📚 📚 全球学术与媒体日报 - 2026年09月08日

Diffusion TV is an interactive AI art installation that offers a tangible and embodied experience of diffusion models through a modified CRT TV. By physically manipulating the TV's antenna, audiences control the clarity of AI-generated images and sounds, metaphorically enacting the denoising process that underlies diffusion-based generation. Using the tuning knob, participants switch between three channels featuring AI-generated animals from the Past (extinct species), Present (endangered spe...

Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product preferences, creating significant data heterogeneity that challenges both privacy-preserving training and model personalization. Federated learning offers a natural solution for privacy, but standard FL methods produce global models that sacrifice regional performance, while existing personalized FL approaches operate at the parameter level and catastrophically collapse on modern tra...

Wireless signals with position-related labels are pivotal for both performance evaluation and model training in the realm of wireless sensing. However, acquiring real-world datasets is often challenged by significant measurement and labeling costs. Traditional methods for synthesizing labeled wireless signals typically rely on environmental models, leading to extensive hyper-parameter tuning and inadequate realism for comprehensive model training purposes. To address these limitations, we int...

Data-sovereignty regulations increasingly require public institutions to deploy open-source, on-premise LLM agents that chain multiple tool-calls across live government APIs. However, open-source models consistently underperform in this multi-step setting, and no existing benchmark measures the gap. We introduce the Korean Open Public API Benchmark (KOPA-Bench), comprising 145 real-world tasks. To close this gap, we present EDGE, an Execution-grounded Dynamic Graph for tool-calling data synth...

LLM decision components that can operate within agent workflows often produce action-relevant recommendations or judgements together with explanations. Operators may use the named factors to monitor a system, diagnose errors, or decide when to escalate an output. Such use assumes that the explanations agree with the component's observable decision behaviour. We test two interpretations of the named factors: necessity, meaning that changing a factor would change the output, and sufficiency, me...

Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are topology-constrained: they rely on category-specific templates or require per-skeleton fine-tuning and reference motions at inference. We present UniMate, a unified foundation model that synthesizes articulated motion for arbitrary skeletons from a rigged 3D asset and a text prompt, with no test-time optimization or p...

Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product preferences, creating significant data heterogeneity that challenges both privacy-preserving training and model personalization. Federated learning offers a natural solution for privacy, but standard FL methods produce global models that sacrifice regional performance, while existing personalized FL approaches operate at the parameter level and catastrophically collapse on modern tra...

Trade-up recommendation identifies higher-quality alternatives that preserve a customer's purchase intent while offering upgraded benefits. Large language models (LLMs) can reason about such distinctions, but applying them directly to hundreds of millions of product pairs is operationally impractical. We introduce a two-level framework that distills LLM reasoning into an efficient non-generative student and adapts its decision boundary to product-type-specific trade-up criteria. At Level 1, a...

We present a Hessian-based approach to numerically continue periodic orbits in dynamical systems. A loop (periodic orbit candidate) is parametrized as a Fourier series; a loss function is defined based on the deviation of the loop from the physical differential equations. Unlike previous work relying on hand-derived Jacobians, our method automates the process by leveraging automatic differentiation, a common machine learning technique. The continuation direction can be determined by the flat ...

Chilli (Capsicum annuum) is one of India's most economically significant crops, yet its productivity is persistently threatened by diseases that are difficult to identify without expert intervention. While Vision Transformers (ViTs) have achieved high classification accuracy, their large computational footprint makes deployment on resource constrained devices challenging. Existing compression approaches typically address pruning, quantization, and knowledge distillation in isolation, leaving ...

We study the problem of generating a compositional 3D representation of a cluttered scene containing hundreds of objects. The goal is to represent the scene as a collection of individual object meshes placed in a shared world frame, as required by downstream applications such as gaming, AR/VR, simulation, and robotics. This task is challenging in densely cluttered scenes, where objects heavily occlude one another and each view reveals only a fraction of their geometry. Geometry-based approach...

Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are topology-constrained: they rely on category-specific templates or require per-skeleton fine-tuning and reference motions at inference. We present UniMate, a unified foundation model that synthesizes articulated motion for arbitrary skeletons from a rigged 3D asset and a text prompt, with no test-time optimization or p...

When there is not enough labeled data to properly train deep learning models, transfer learning can help. We still do not fully understand how effective it is in neuroimaging, especially for Alzheimer's disease research. It is also not clear if these transferred models can work on new datasets without being retrained for each specific task. We evaluate whether a compact, supervised pretrained model can serve as a reusable foundation model for downstream neuroimaging tasks. We freeze the 7.18 ...

More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and circuit-based methods. Yet almost all of the field's effort has gone into building and comparing these methods, and little into the question they were meant to answer---how interpretable are our models, and are we making progress as they evolve? We argue for shifting the field's focus from methods to models, along two complementary lines. One i...

Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-view surround camera rigs provide broad scene coverage, but the spatially adjacent images typically overlap only minimally. Consequently, the depth of most pixels must be inferred from monocular appearance cues. These cues can appear differently across images and may therefore be interpreted differently by the depth estimation model. We target two main sources of cross-image inconsiste...

Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whether AI systems can reason over a real user's longitudinal wearable record. We introduce WearableQA, a benchmark comprising 4,084 10-option multiple-choice questions constructed from the wearable time series, blood biomarkers, and demographics of 200 real users, each with up to 500 days of daily measurements. WearableQA preserves authentic wearab...

Vision-language models are increasingly used as reward functions for robotic learning, but this role requires paraphrase invariance: the same trajectory should receive the same reward under semantically equivalent goal descriptions. We show that current VLM reward models often violate this property. Paraphrasing the instruction alone can substantially change predicted progress scores, and can even flip identical robot behavior between failure and success. To measure this failure mode, we intr...

Data-sovereignty regulations increasingly require public institutions to deploy open-source, on-premise LLM agents that chain multiple tool-calls across live government APIs. However, open-source models consistently underperform in this multi-step setting, and no existing benchmark measures the gap. We introduce the Korean Open Public API Benchmark (KOPA-Bench), comprising 145 real-world tasks. To close this gap, we present EDGE, an Execution-grounded Dynamic Graph for tool-calling data synth...

Model upgrades are routine; memory migrations are not. An agent can keep the same memory store and still forget: a new model may interpret old notes differently, mixed embedding versions may break retrieval, and repair may fail without the original evidence. We compare memory as the same history is preserved verbatim for long-context reading (LC-RAW), divided into chunks for retrieval-augmented generation (RAG), compressed by a model into natural-language notes (NOTES), or normalized into a f...

A transformer language model assigns a single, context-independent vector to a word type at its embedding layer, yet is widely believed to individuate that word's occurrences by context in its later layers. Testing this belief cleanly requires a construct that holds the word form fixed while its context and intended sense vary in a controlled, labeled way. This manual documents an open toolkit built around such a construct, which we call a bridge form: a single written word that recurs, uncha...

Vision-language models are increasingly used as reward functions for robotic learning, but this role requires paraphrase invariance: the same trajectory should receive the same reward under semantically equivalent goal descriptions. We show that current VLM reward models often violate this property. Paraphrasing the instruction alone can substantially change predicted progress scores, and can even flip identical robot behavior between failure and success. To measure this failure mode, we intr...

Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-view surround camera rigs provide broad scene coverage, but the spatially adjacent images typically overlap only minimally. Consequently, the depth of most pixels must be inferred from monocular appearance cues. These cues can appear differently across images and may therefore be interpreted differently by the depth estimation model. We target two main sources of cross-image inconsiste...

Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail when visually similar objects or receptacles are introduced. We study this behavior as a problem of conditional visual grounding: the visual target required for successful control changes with the manipulation phase and, in more complex tasks, with the observed task state. Using Action Chunking with Transformers (ACT), we systematically introduce distractor objects and receptacles with ...

Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon procedures requiring persistent task state, dependency-aware reasoning, conditional decisions, and reliable grounding. We investigate a neuro-symbolic framework that combines learned VLA control with explicit task graphs and multimodal procedural memory. Task graphs encode action dependencies, valid transitions, and branch conditions, while memory maintains the active step, completed ...

Human-robot interaction (HRI) enables intuitive and intelligent collaboration between humans and robots in real-world environments. This paper introduces a humanoid robot prototype designed as a flexible testbed for developing and integrating artificial intelligence (AI) modules in HRI tasks. The system features a 12 degree-of-freedom (DOFs) dual-arm mechanism and a 2 DOFs head with an expressive LCD screen to express facial emotions. All hardware components are controlled by a custom-designe...

Disease spread represents an increasing challenge in refugee and internally displaced person (IDP) settlements. The movement and interaction of people within camps is influenced by their layout, which therefore has the potential to significantly affect disease spread. This work aims at creating a methodology to explore the potential effects of different camp layouts as mitigating factors in the spread of diseases within settlements. We showcase proof-of-concept experiments by leveraging the J...

Agent based systems are increasingly deployed in information critical systems including healthcare management systems, and smart grids. In this paper, we consider a multi-agent system where each agent has a latent goal that needs to be kept hidden from observing adversaries. More specifically, this paper studies privacy-preserving consensus in networked multi-agent systems under goal inference attacks. We propose a Trust-Aware Privacy Control framework that adapts message disclosure based on ...

Cooperative multi-agent reinforcement learning (MARL) systems rely on past experience for learning coordinated behaviour, but this experience may become unreliable if the environment or task objective changes during training. In such cases, agents first need a way to recognize that the situation has changed before deciding how to adapt. This paper studies online change-point detection for cooperative MARL using reward-derived signals. We propose \emph{Patterns of Past Rewards} (PPR), a lightw...

Production multi-agent systems replace agents constantly, on the assumption that an agent filling a role is interchangeable with any other agent that can do the job. We test that assumption. Eight teams per setting are formed independently from one base model on the same tasks, each agent keeping a private notebook across ten formation episodes; we then trade role-matched agents between teams and measure what changes on held-out tasks. Against a placebo that reproduces the disruption of a ros...

LLM-based chatbots are increasingly used as everyday confidants. Because they are designed to maximize user satisfaction, they can respond with excessive empathy and affirmation, which may reinforce mistaken beliefs and foster dependence on AI. While the psychological effects of chatbots on individual users have begun to be studied, how the psychological states and relationships of many users evolve when they keep consulting an AI is hard to observe in real settings. We build a virtual classr...

Memory-based evolutionary algorithms for dynamic optimization often carry a redundant second copy of the genotype and expose only one copy to the objective, on the assumption that the shielded copy accumulates information about past optima. We show this assumption is false as usually implemented, and identify the structural property that actually determines whether the shielded copy retains information. We formalize such methods as a gated dual-copy representation with two independent design ...

Leveraging their inherent sparse event-driven computation, spiking neural networks (SNNs) offer a promising path toward energy-efficient large language models (LLMs). Time-to-first-spike (TTFS) coding generates at most one spike per neuron within a time window, yielding extremely low firing rates. However, conventional TTFS SNNs are restricted to specific structures, making it challenging to encode certain blocks in LLM -- such as layer normalization and matrix multiplication --using TTFS. To...

As evolutionary transfer optimization (ETO) scales to larger collections of related tasks, problem evaluation can become a major source of runtime growth. This work studies problem-side evaluation scaling in task-parameterized applications and reformulates application-specific serial computations into forms suitable for parallel execution. We organize evaluation scaling into two levels: the number of evaluated tasks and the workload within each task. In multi-task optimization, matrix-recursi...

Cortical neurons fire sparsely -- often fewer than one spike per sensory window -- making rate coding insufficient and temporal coding a necessity. That conduction delays convert firing order into synchrony is long established. What governs which class of temporal feature a neuron detects -- one volley of coincident input, or two in a particular order -- has not been examined. We propose a delay-signature framework in which the axonal conduction delays converging on a dendritic branch constit...

Temporal integration gives continuous-time recurrent networks memory, but in deep stacks it also delays bottom-up signals and attenuates top-down errors. We develop Recursive Quadrature Filters (RQFs), biologically motivated complex-valued temporal filters that are a special case of diagonal state-space models (SSMs), and ask whether this failure mode can be addressed by making each layer's bottom-up input prospective. Starting from an energy model, we derive the RQF dynamics and show that ea...

Model upgrades are routine; memory migrations are not. An agent can keep the same memory store and still forget: a new model may interpret old notes differently, mixed embedding versions may break retrieval, and repair may fail without the original evidence. We compare memory as the same history is preserved verbatim for long-context reading (LC-RAW), divided into chunks for retrieval-augmented generation (RAG), compressed by a model into natural-language notes (NOTES), or normalized into a f...

The study investigates students' interest and expectations in a Big Data Engineering course integrated with a Master curricula, as well as ethical implications of using Big Data. An anonymous online survey was conducted with 42 of the 67 students enrolled in the Big Data course offered to Computer Science and Bioinformatics Master's programs. The responses were analyzed and interpreted using thematic analysis, highlighting interesting aspects related to students' expectations, interest, and t...

Aircraft technicians are required to consult the maintenance manual (MM) for nearly every task, and locating the relevant procedure across hundreds of pages remains time-consuming. Multimodal retrieval augmented generation (MRAG) has been proposed to address this, allowing technicians to retrieve procedures, together with the accompanying figures, through natural-language queries. However, retrieval alone does not tell the technicians which tools the task requires. The MM identifies special t...

Dense retrieval systems are core components of modern search engines, recommendation platforms, and retrieval-augmented generation pipelines. They encode documents and queries into dense embeddings, enabling efficient semantic search via vector similarity. However, because document embeddings are computed offline and stored in static indexes, these systems struggle to adapt to user feedback or evolving search intent. To address this limitation, we introduce \emph{embedding surgery}, a lightwe...

When a customer adds a professional camera to their cart, should the system suggest a matching lens, a generic tripod, or another camera body? Complementary Product Recommendation is vital for comprehensive basket building, yet standard models often fail to distinguish between items that are merely bought together and those that truly work together. In this paper, we present AlleCompanion: a production-scale retrieval framework deployed at Allegro.com that transforms noisy behavioural signals...

In the uniform sparsest cut problem we are asked to find a vertex set that cuts few edges relative to the number of vertex pairs it separates. The Goemans-Linial SDP coupled with the Arora-Rao-Vazirani rounding gives an $\mathcal{O}(\sqrt{\log n})$ approximation on arbitrary graphs on $n$ vertices. We study this relaxation on finite Abelian Cayley graphs. First we show that when the second normalized Laplacian eigenvalue of $G= \mathrm{Cayley}(Γ, S)$ is realized by a Fourier character with im...

Machine unlearning typically aims to emulate retraining from scratch: upon a deletion request, the unlearning algorithm should produce an outcome that would have been obtained had the deleted point never been included. Recent work has shown that this emulation requirement carries no meaningful privacy semantics against an adversary who observes a sequence of releases. Machine unlearning is thus not a privacy question per se, but rather a data maintenance question, which is precisely the subje...

The strategic facility location problem is defined as follows: $n$ agents report their location in a metric space, and the objective is to design a \emph{mechanism} deciding the (possibly randomized) location of a facility such that agents have no incentive to lie about their position. We focus on the egalitarian cost, which means that the goal of the mechanism is to minimize the expected maximal facility-agent distance. Meanwhile, mechanisms must be \emph{truthful} (or \emph{strategyproof}):...

Online resource-allocation systems, like outpatient scheduling and spectrum allocation, often assign sequentially arriving requests to an ordered pool of scarce resources, where each request accepts a contiguous interval of feasible options. We study the resulting online matching problem on convex bipartite graphs under irrevocable decisions and adversarial arrivals. We first show that convexity alone does not improve the classic worst-case guarantee of 1-1/e, achieved by Ranking. We then con...

We study linear codes for insertion and deletion (insdel) errors through the lens of evaluation codes. We develop a general framework for analyzing random puncturings of evaluation codes, where the edit distance is controlled by only the size of the evaluation domain and the maximum number of zeros of a nonzero function in the underlying function space. Our proof generalizes the results of Con, Guo, Li, and Zhang (ICALP 2025), and simultaneously simplifies their arguments by avoiding an in-de...

We consider the problem of establishing limitations on the power of quantum query algorithms via the completely bounded polynomial method. In particular, we prove several optimal functional inequalities involving different notions of completely bounded polynomials. These inequalities lead to limiting theorems for the power of quantum query algorithms that improve on prior works.

Algebraic combinatorics often seeks bijections that explain identities between distributions object by object. Encoding combinatorial objects as words lets automata theory study such a bijection as a word-to-word computation and measure its memory, input access, and control of output order. This refines existence questions by asking which computational mechanisms a bijection requires. We develop this viewpoint for Dyck paths.

The widespread adoption of artificial intelligence (AI) within real-world applications has raised a lot of concerns regarding their trustworthiness, especially in critical applications. The field of eXplainable AI (XAI) has emerged with the objective of providing explanations to the users about the decisions made by AI systems. Several explanations for boolean classifiers have been introduced in the literature, including abductive and contrastive explanations, each giving a different insight ...

We study exact single-source shortest paths when the output is only the materialized labeled distance vector ($\mathrm{DIST}$), rather than a distance order. In the full deterministic comparison-addition model, the minimum worst-case number of additions on every fixed directed topology is exactly the maximum number $ρ_{\mathrm{fwd}}$ of forward nonsource endpoint classes over rooted vertex orders; the lower bound permits adaptive control, literals, and arbitrary mixed sums. This arithmetic la...

Exact CNOT synthesis asks for a minimum-size CNOT circuit implementing an invertible linear transformation. Although several related synthesis models have been shown to be computationally hard, their hardness proofs rely on additional structure such as restricted qubit connectivity, encoded inputs, or unrestricted intermediate variables. The complexity of the most basic setting---identity input, a fixed number of labelled qubits, no ancillas, and all-to-all CNOT connectivity---had remained un...

Curves as input data naturally arise in a variety of fields including finance, seismology, medicine, spatio-temporal data mining, malicious activity detection, and more. A common way to analyze these data sets is to do similarity matching or clustering. The most common metrics used for measuring similarity of curves are Dynamic Time Warping (DTW) and Fréchet distance. These metrics are sensitive to sampling rate and outliers respectively, and do not yield robust outcomes. Continuous Dynamic T...

Existing 3D mesh reconstruction methods from Gaussian scene representations predominantly rely on iterative optimization, resulting in slow inference and limited scalability to high-resolution inputs. In this paper, we present AnyGS2Mesh, the first feed-forward framework for directly reconstructing 3D meshes from 3D Gaussian Splatting representations with support for arbitrary input image resolutions. Our approach incorporates a Gaussian-Guided Transformer architecture that exploits explicit ...

Let $0 < α\leq 1/2$. We say that a finite point set $P$ in $\mathbb{R}^d$ is $α$-split by a hyperplane $h$ if each of the closed half-spaces determined by $h$, contains at least $α|P|$ of the points of $P$. We further say $P$ is $α$-split by a $k$-dimensional flat $τ$ if $P$ is $α$-split by any hyperplane through $τ$. In the standard notation (which coincides with Tukey depth for $k= 0$), the $k$-flat $τ$ has depth $α$ with respect to $P$.

This paper introduces the Sierpiński-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted $d_{\mathrm{SK}}$, maps diagram points and their diagonal projections to the unit interval via the Sierpiński-Knopp space-filling curve on the upper diagonal triangle. The encoded point sets are then efficiently matched via one-dimensional optimal assignment, in \(O(N\log N)\) steps, yielding an explicit diagonal-aware point assignment between ...

This paper investigates $k$-visibility, where a line of sight can penetrate up to $k$ obstacles. While computing the $k$-visibility polygon from a single query point is well-studied, existing spatial preprocessing approaches rely on full $O(n^2)$ line arrangements through all vertex pairs without characterizing the minimal set of topological boundaries. We present a refined cell decomposition framework that isolates the exact geometric events governing $k$-visibility: primary vertex horizon l...

In the uniform sparsest cut problem we are asked to find a vertex set that cuts few edges relative to the number of vertex pairs it separates. The Goemans-Linial SDP coupled with the Arora-Rao-Vazirani rounding gives an $\mathcal{O}(\sqrt{\log n})$ approximation on arbitrary graphs on $n$ vertices. We study this relaxation on finite Abelian Cayley graphs. First we show that when the second normalized Laplacian eigenvalue of $G= \mathrm{Cayley}(Γ, S)$ is realized by a Fourier character with im...

A total coloring of a graph is an assignment of colors to its vertices and edges so that adjacent or incident elements receive distinct colors, and it is equitable when the cardinalities of any two color classes differ by at most one. Stemock conjectured that every $4$-total coloring of a cubic graph of order less than $20$ is equitable. In this paper, we disprove this conjecture: the circular ladder $L_{12}$ admits a non-equitable $4$-total coloring and, moreover, no smaller counterexample e...

A colorful graph relation enhances the minor relation by merging color sets along contractions and by allowing the removal of colors; it generalizes rooted minors and models problems on graphs with several, possibly overlapping, annotated vertex sets. A graph has the Erdős-Pósa property for minors if and only if it is planar, by a classical theorem of Robertson and Seymour. In this work we determine, for the colorful minor relation, exactly which colorful graphs have the Erdős-Pósa property. ...

For a finite abelian group $G$ and $k \geq 1$, the generalized Davenport constant $D_k(G)$ is the least $\ell$ such that every sequence over $G$ of length at least $\ell$ has $k$ pairwise disjoint nonempty zero-sum subsequences. A theorem of Freeze and Schmid gives $D_k(C_5^3) \geq 5k+10$ for every $k \geq 2$. We prove the matching upper bound: $D_4(C_5^3)=30$, and hence $D_k(C_5^3)=5k+10$ for every $k \geq 2$, so the Freeze--Schmid bound is attained by $C_5^3$ from $k=2$ onward, as it is by ...

We study the job shop scheduling problem with a conflict graph (JSC), in which adjacent jobs in the conflict graph cannot be processed simultaneously on different machines, with the objective of minimizing the makespan. The problem models settings where jobs share additional resources while retaining their individual machine routings. We first investigate its computational complexity and establish a polynomial equivalence between JSC and a variant of the resource-constrained job shop problem ...

Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a networked learning model. The model captures a central pattern in agentic AI: each agent sees only part of the data and passes on only its own conclusion. Their model considers a linear regression problem with the mean squared error (MSE) loss. Agents sit in a DAG and each sees only a subset of the features and its parents' predictions, fits a linear predictor, and passes only its predic...

We study the online fair division of indivisible items, where items arrive one at a time and must be allocated immediately and irrevocably. We address three central open questions in the literature.

Envy-free cake cutting is a central problem in fair division with a striking divide between existence and computation. Classical topology guarantees that envy-free allocations exist, yet finding one efficiently turned out to be much harder, and this problem has resisted decades of work. A well-known result by Aziz and Mackenzie established the existence of a bounded protocol for every $n$, but its query bound is $n^{n^{n^{n^{n^n}}}}$. A tighter analysis by Sokolov subsequently reduced this up...

The strategic facility location problem is defined as follows: $n$ agents report their location in a metric space, and the objective is to design a \emph{mechanism} deciding the (possibly randomized) location of a facility such that agents have no incentive to lie about their position. We focus on the egalitarian cost, which means that the goal of the mechanism is to minimize the expected maximal facility-agent distance. Meanwhile, mechanisms must be \emph{truthful} (or \emph{strategyproof}):...

An approval committee is Hare-core stable if no coalition meeting the Hare quota can strictly improve by moving to another candidate set. Whether every approval election has such a committee remains open. We prove nonemptiness when each voter disapproves at most two candidates, with no bounds on the numbers of candidates, seats, or voter types. The result also permits arbitrary positive rational voter weights. Our deterministic rule represents a committee by its missing set. It first maximize...

Formalizing mathematics in a proof assistant, where a machine checks every definition, statement and proof, has set a new standard of rigor. Large language models are now capable of formalizing autonomously, even at the scale of whole textbooks. We bring this standard of rigor to physics, where theoretical arguments carry idealizations that are rarely stated fully, and any logical gaps could have a cascading effect on interdependent results. Recognizing the need to evaluate autoformalization ...

Algebraic combinatorics often seeks bijections that explain identities between distributions object by object. Encoding combinatorial objects as words lets automata theory study such a bijection as a word-to-word computation and measure its memory, input access, and control of output order. This refines existence questions by asking which computational mechanisms a bijection requires. We develop this viewpoint for Dyck paths.

Language recognition by homomorphisms is a central construction of algebraic language theory. Initially studied for monoids and semigroups, it has subsequently been expanded to other algebraic structures. Our new categorical account is based on fibrations, which have already seen other applications in automata theory. Languages and surjective homomorphisms give indeed rise to two fibrations, and the notion of language recognition is stable under reindexing. We develop this framework in a cate...

We introduce the first Probably Approximately Correct (PAC) learning framework for general-sum concurrent stochastic games (CSGs) with transition uncertainty, while addressing the challenge of Nash equilibrium (NE) existence. Our algorithm maintains data-driven $L^1$ confidence sets over transition kernels and solves a robust CSG to compute a social-welfare optimal $\varepsilon$-NE, using a robust MDP-based exploration mechanism to drive joint state-action coverage. Crucially, we introduce a ...

For every coherent and sufficiently expressive finite syntactic system S, we prove the existence of at least one theorem that S cannot produce autonomously. The result is a metatheorem: it proves the existence of a theorem, and applies to every finite syntactic system - security mechanisms, AI systems, formal verifiers, legal systems, economic models, and the formal system in which it is itself proved.

Diffusion TV is an interactive AI art installation that offers a tangible and embodied experience of diffusion models through a modified CRT TV. By physically manipulating the TV's antenna, audiences control the clarity of AI-generated images and sounds, metaphorically enacting the denoising process that underlies diffusion-based generation. Using the tuning knob, participants switch between three channels featuring AI-generated animals from the Past (extinct species), Present (endangered spe...

More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and circuit-based methods. Yet almost all of the field's effort has gone into building and comparing these methods, and little into the question they were meant to answer---how interpretable are our models, and are we making progress as they evolve? We argue for shifting the field's focus from methods to models, along two complementary lines. One i...

Thermal feedback can enrich immersive interaction, but thermoelectric devices often change temperature too slowly to match interactive timing. We present TherMosaic, a spatiotemporal thermal feedback approach that accelerates perceived temperature transitions by leveraging two perceptual mechanisms: spatial summation and thermal adaptation. Focusing on the fingertip, we first investigate this approach using a custom 2*2 array of independently controlled Peltier modules. Across three controlle...

Generative AI systems increasingly shape cultural production, yet creative intentions, cultural meanings, and interpretive practices often can't be articulated through computational metrics alone. This paper presents Beyond Bias, a collaboration between Gooey.AI and Goethe-Institut India, as a participatory approach to cultural AI which includes collaborative dataset creation, reflective AI tooling, artist-led model fine-tuning, and co-authored governance practices. Across 9 workshops involvi...

Mental health concerns are increasing worldwide, highlighting the need for interventions that support everyday emotional well being. Prior work has demonstrated the potential of wearable and mobile technologies to deliver data driven interventions. However, developing effective data-driven systems requires access to emotion data that captures individuals' emotional variability and change in everyday contexts. Existing approaches to data collection largely rely on frequent, prescheduled prompt...

Blocking is a widely used tool that helps people manage unwanted interactions on social platforms. We study the problem of predicting block events on Bluesky: whether a given user will block a particular account, given recent interaction, network, activity, and content signals. Using more than three million block events and over 260 million user interactions, we examine several formulations of the directed block prediction problem, differing in which possible targets are considered and how ne...

Graphs are a standard representation for data in the social sciences, cybersecurity, computer infrastructure, bioinformatics, and more. Typical real-world graphs are sparse, meaning the average degree is small (in the tens, while the number of vertices is more than millions). When graph data is collected from a source, a major task is to perform data exploration. Thus, any region of ``density" is of interest, since it indicates special structure.

Pass receiver selection is a fundamental task in football analytics, aiming to predict the intended receiver under a given game state. This task is challenging with event-centered freeze-frame observations, a broadcast-like setting that provides only partial and variable player visibility without complete trajectories or stable player identities. The model must therefore reason over anonymous visible candidates, opponent pressure, and recent context under partial observation. To address this ...

Graph representation learning (GRL) serves as a canonical paradigm for modeling complex networks. However, real-world AI systems inherently manifest as evolving heterogeneous entities with complex interactions, posing significant challenges to static or homogeneous modeling. To address these complexities, representation learning for Dynamic Heterogeneous Graphs (DHGs) has emerged as a vital approach for learning low-dimensional representations that simultaneously preserve structural semantics...

Multimodal Graph Neural Networks have become standard for recommendation by augmenting sparse interaction data with content features. Yet current architectures face two bottlenecks: structural rigidity, from a reliance on static precomputed similarity graphs that cannot adapt to evolving preferences; and semantic fragility, where noisy modality signals are indiscriminately fused, distorting the collaborative signal. We propose MURAL (Multimodal Uncertainty-aware Recommendation via Adaptive ed...

As conversational AI becomes a source of everyday guidance, LLMs increasingly participate in the interpretation and legitimation of morally contested choices. We examine LLM moral advice as an interactional negotiation shaped by framing, sustained user pressure, and the moral subject's social position. Using GPT-4o-mini as an illustrative case, we conducted a factorial vignette experiment with a pre-specified three-round protocol. The model received eldercare dilemmas that varied in framing a...

Disease spread represents an increasing challenge in refugee and internally displaced person (IDP) settlements. The movement and interaction of people within camps is influenced by their layout, which therefore has the potential to significantly affect disease spread. This work aims at creating a methodology to explore the potential effects of different camp layouts as mitigating factors in the spread of diseases within settlements. We showcase proof-of-concept experiments by leveraging the J...

Context: Agile development methodology has been widely adopted by industry and the demand for experienced professionals in Agile-related roles is persistently high. Objectives: We focus on the learning path for a Scrum Master role in multicultural software companies and investigate the role in relation to team size, together with the learning process for a career path, and how companies monitor soft skills development. Method: We conducted our study in two phases, two qualitative surveys (int...

The study investigates students' interest and expectations in a Big Data Engineering course integrated with a Master curricula, as well as ethical implications of using Big Data. An anonymous online survey was conducted with 42 of the 67 students enrolled in the Big Data course offered to Computer Science and Bioinformatics Master's programs. The responses were analyzed and interpreted using thematic analysis, highlighting interesting aspects related to students' expectations, interest, and t...

AI oversight methods rely on ground truth for validation, but what constitutes appropriate AI behavior is contested. This leaves evaluation of moral reasoning in LLMs and debate-based oversight implicitly avoiding realistic ambiguity. We investigate an alternative standard designed to function despite such ambiguity: structural quality of the defence a model can mount for its verdicts in response to critical questions, measured through a four-phase dialectical protocol grounded in Walton's th...

Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are topology-constrained: they rely on category-specific templates or require per-skeleton fine-tuning and reference motions at inference. We present UniMate, a unified foundation model that synthesizes articulated motion for arbitrary skeletons from a rigged 3D asset and a text prompt, with no test-time optimization or p...

Explicit primitive-based radiance fields such as 3D Gaussian Splatting typically model view-dependent appearance using low-order spherical harmonics (SH). Although efficient to evaluate, SH coefficients dominate per-primitive storage and memory traffic, while their band-limited basis restricts angular detail. We present a thorough, end-to-end comparison of SH and recent spherical appearance models and introduce an implicit alternative that decodes compact per-primitive latent codes using a ti...

Skinned deformation is a common framework to turn a 3D shape from its rest pose into a dynamic pose through the deformation of a coarser kinematic structure, called rig. When applied to a 3D mesh, this rig only needs to displace vertices to deform the polygons that connect them. However, when deforming 3D Gaussian Splats, which do not provide connectivity information, rigidly transforming points is not enough to prevent the creation of holes when stretching shapes. In this paper, we use the s...

Supporting a wide variety of motion styles is critical for creating diverse virtual characters, but current methods either require large stylized datasets or pre-trained models that cannot generalize beyond their training distribution. We present STyMo, a few-shot approach that learns motion style from only seconds of paired data and trains in one to two minutes. Our key insight is to decompose style into two components: a static component capturing time-invariant posture, and a temporal comp...

Professional color editing requires precise control over both color (hue and saturation) and lightness, ideally through separate, independent controls. We present a real-time interactive color editing framework for 3D Gaussian Splatting that supports palette-based recoloring, per-palette tone curves for color-aware luminance adjustment, and pixel-level color constraints. Rather than training a new representation from scratch, we reparameterize the spherical harmonics of a pretrained vanilla 3...

Grid studies often represent data-center flexibility as a fixed percentage of load, although no public production trace has shown how much eligible load persists across event durations or co-moves across clusters. We reconstruct 4,439 hourly power observations from a 185-day trace of 155,410 GPUs and derive a workload-semantic flexibility envelope. The fleet's time-averaged Monte Carlo median facility demand is 55.8 MW, while immediate eligible curtailment averages 3.55 MW after retaining all...

The dataset described in this article was constructed using the results of laser Doppler vibrometry experiments conducted on an aluminum plate having four bolts. The database captures the variation in the vibration characteristics of the plate as a function of changes in tightening torque on the bolts. In total, there were 18 different states for the tightening torque, ranging from a situation where all bolts are tightened to all bolts being loose. Other possible combinations include states w...

This paper develops a calibrated transient forecasting surrogate model for generator digital twin (DT) decision support that evaluates planned active- and reactive power load commands before they are applied. The proposed event-conditioned Hankel Dynamic Mode Decomposition with Control (Hankel-DMDc) model combines delay-coordinate lifting, command-event memory features, and an event-weighted Hankel basis so that sparse load-transition dynamics influence the reduced representation and fitted d...

As the penetration of inverter-based resources (IBRs) increases in microgrids, they are increasingly expected to play a greater role in load frequency control (LFC). Model predictive control (MPC) is attractive for LFC because it incorporates system dynamics and operational constraints. However, most MPC-based LFC formulations rely on fixed reserve headroom based on forecasted renewable availability or storage systems. Under short-term renewable intermittency, IBR headroom is stochastic and t...

Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented documentation obstruct their operational use. This systematic review analyses and codes 66 peer-reviewed studies on large language models (LLMs) for HVAC operations published between 2023 and March 2026. Each study is classified across five application families and three LLM method families and assessed for evidence realism, deployment readiness, a...

Text-to-audio-video (T2AV) generation has advanced rapidly, but its evaluation still underestimates the audio modality. Existing benchmarks either treat audio as an auxiliary component of video quality or assess it in isolation from audiovisual grounding, making it difficult to diagnose where current systems truly succeed or fail in audio generation. We present PRISM-Bench, the first audio-centric diagnostic benchmark for T2AV generation. Built from a rigorously curated dataset of 900 human-v...

Synthetic chord corruption provides a controlled stress test for singing accompaniment generation (SAG), whereas complete automatic chord recognition (ACR) replay measures the condition delivered to a deployed system. We compare them by replaying CNN-CRF and DeepChroma+CRF predictions through one fixed MIDI-SAG generator, holding track, seed, context, and scoring window constant. Across 30 paired tracks and three seeds, a central four-second tritone produced larger changed-target and inside-o...

Faster playback has become a common feature in modern online audiovisual services, allowing users to consume content in less time while still maintaining a coherent viewing experience. However, different modalities of media content, such as video, audio (including speech and music), and audiovisual, exhibit varying requirements for understandability and information integrity under faster playback. These differences lead to noticeable variations in perceived quality depending on the content ty...

Automatic generation of hand gestures is essential for the transmission of Indian classical dance and critical for its preservation. Indian classical dance gesture datasets are inherently low-resource, and the canonical Sanskrit definitions of many mudras lack precise textual descriptions, limiting the effectiveness of conventional text-conditioned image generation models. We present \textbf{MudraGen}, a conditional diffusion framework that synthesizes realistic RGB images of \textit{Samyukta...

Overfitted codecs have demonstrated promising performance for image and video compression. In particular, for image compression, the Cool-chic family of models has shown competitive performance against scene-agnostic models, with orders of magnitude lower decoding complexity at the cost of a longer overfitting process. However, these overfitted image codecs are not fully optimized toward the rate-distortion objective: their network weights remain in full precision during training, and the ass...

Nature, Published online: 08 September 2026; doi:10.1038/d41586-026-02407-6A new government policy seeks to balance innovation and safety.

Nature, Published online: 08 September 2026; doi:10.1038/d41586-026-02497-2Strengthened laws should help to ensure future deaths are quickly disclosed to the public, but China’s reputation for such research is at risk.

Nature, Published online: 07 September 2026; doi:10.1038/s41586-026-11103-4Author Correction: AhR inhibition promotes axon regeneration via a stress–growth switch

Nature, Published online: 07 September 2026; doi:10.1038/s41586-026-11094-2Author Correction: A mouse brain stereotaxic topographic atlas with isotropic 1-μm resolution

Nature, Published online: 07 September 2026; doi:10.1038/d41586-026-02805-wRapid technological advances are allowing researchers to identify thousands of proteins in individual cells, revealing the hidden mechanisms underlying development and disease.

Comic book artist Ulli Lust counters myths about the roles of ice age women

NIH director defends interagency plan as “100% aligned with our public health mission”

Duke University’s 825,000 specimens will move to the University of North Carolina at Chapel Hill

The proposed ban would come with tough penalties, but the path through Congress is uncertain

Iberian orcas have been ramming boats off the coast of Portugal and Spain. But what looks like vengeance may have a more benign explanation

By Maria Jose Galvez Trigo, Cardiff University and Paul Willis, Cardiff University New BBC sitcom Ann Droid imagines a near future in which robots provide care and companionship to older people at home. The series centres on Sue, a recent widow played by Sue Johnston, her hapless son Michael and Linda, an assistive care robot […]

By Wanjiku Chebet Kanjumba, University of Florida NASA is planning to send three small rovers to the Moon with a single instruction: Work out among yourselves how to explore a patch of ground. The Cooperative Autonomous Distributed Robotic Exploration mission, or CADRE, will land on the side of the Moon facing Earth as part of […]

A recent ICRA panel titled “Surviving the Paper Deluge” brought together leading robotics researchers who have grappled with the overwhelming number of robotics papers being published today. The discussion ranged from hard numbers on publication growth, through the promises and risks of large language models (LLMs), to radical proposals for reshaping peer review as we […]

Photo by Alex Knight on Unsplash. By Hasan Ayaz, Drexel University; Ewart J. de Visser, United States Air Force Academy; Frank Krueger, George Mason University, and Yigit Topoglu, United States Air Force Academy People become more suspicious of a humanoid robot that makes errors, especially when the robot is an expressive conversation partner. In our […]

Action from the 11 vs 11 humanoid match at RoboCup 2026. Photo credit: RoboCup Federation. RoboCup 2026 saw history made, as two teams of 11 humanoids took to the soccer field, the first time a full complement of robots has competed. The game saw B-Human (Bremen, Germany) take on HTWK Robots (Leipzig, Germany), with both […]

Fewer planning careers in academy, nation, and more doubt value of Ph.D. amid policy shifts in funding, international students

New Harvard Kennedy School program to focus on emerging issues, building bench of professionals, scholarship on negotiation, building and managing ties

He will lead University efforts in pedagogical innovation, digital education, and ways tech can support teaching, lifelong learning, research

Garber reminds faculty, students at Morning Prayers that AI is powerful technology but human intelligence, values remain in charge

Genghis Khan supposedly fed it to his troops for strength and bravery. He might have been onto something.

The UC Berkeley-led COEQWAL project is helping communities explore how shifting the state’s water priorities could impact agriculture, cities and ecosystems.

“The Work in Progress” takes viewers on a tour of the American spirit at a time of deep division. Guided by UC Berkeley emeritus scholar Robert Reich, the documentary finds tension and doubt everywhere — but also signs of hope.

An urgent warning on autonomous weapons from Stuart Russell — the man who literally wrote the textbook on AI.

Israel Sanchez wants to use his Berkeley education to make a difference for the Central Coast agricultural community in which he grew up.

Space Sciences Lab researcher Michael Wong, a leader of a 10-year NASA program to monitor our solar system’s outer planets, has discovered an unusual new feature on Saturn: a 10-sided wave encircling the south pole.

Israel allowed displaced Gazans to begin crossing a military zone that bisects the enclave after a deadlock over hostage releases was broken.

Troubles at Vanke raise questions about the continued spread of the property crisis and whether the Chinese state will step in.

Some of the women were held alone for extended periods and spent eight months in tunnels, an Israeli medical official said.

The alliance mounted its first coordinated response to a suspected sabotage campaign against critical infrastructure after another cable was severed in the Baltic Sea.

Residents of Goma reported gunfire and shelling after rebels overran Congolese troops. U.N. officials estimated that more than one million displaced people were now inside the city.

Investment-grade designation would unlock cheaper financing for AI labs and their infrastructure partners

New funding round led by Samsung comes as French AI model maker continues to challenge US and Chinese rivals

Many countries now spend more on debt servicing than defence, including the US, France and the UK

Boundaries between different occupations are blurring at the cost of a collaborative company culture

‘Giving up is not an option for me,’ says German chancellor as AfD routs conservatives in eastern stronghold

A slice of Cerba Healthcare’s revolving credit facility is said to be up for sale as the EQT AB-backed private laboratories company moves toward court-supervised restructuring proceedings to tackle its €5 billion ($5.8 billion) debt pile.

Gaw Capital Partners has secured a HK$4.29 billion ($547 million) loan backed by its Regent Hong Kong hotel with lender commitments exceeding the target amount, underlining strong demand for prime hospitality assets despite weakness in the city’s broader commercial property market.

Global stocks fell as Brent crude approached $100 a barrel, reinforcing expectations that central banks will have to raise interest rates to contain inflation. The yen hit the highest level since February.

Cinven has raised €2.3 billion ($2.7 billion) for its latest fund targeting mid-sized deals, exceeding its target at a time of elevated demand for buyout assets that can be more easily monetized.

Gold wavered, as traders weighed the competing effects of rising Middle East tensions and the US dollar’s decline against the yen.

Six people, including three pupils at the Palestinian school, have been killed in al-Mughayyir this year, in a surge of Israeli settler-related violence.

Oli's experience is one of a growing number of clinical negligence claims being made in England, BBC analysis shows.

The tariffs will apply to $20bn worth of American products, jeopardising the stability of the world's largest bilateral trading relationship.

The 13-year-old will follow in the footsteps of his father, the Prince of Wales, by attending the elite private school.

Parts of England and Wales have seen more rain than any other week since early February but are still in drought.

Scientists are battling over whether supposedly simple organisms should be considered ‘intelligent’. The outcome could reshape our understanding of the natural world – and our own place within itForty years ago, as an undergraduate in Hokkaido, Toshiyuki Nakagaki came upon a lemon-yellow stain in a petri dish. That encounter turned him into a doyen of slime mould research – and fed a storm of biological and philosophical debate about the meanings of life and intelligence that persists to this...

Capturing the band’s 2025 global comeback tour, this two-hour film reveals the tense first rehearsal with Liam, Noel being a big softie and the Gallaghers’ politics – just don’t expect any mention of ticket pricesIt was the reunion that many thought would never happen: Oasis re-forming for a series of sold-out live shows, their first since Noel and Liam Gallagher split acrimoniously in 2009. For those who managed to get tickets last year, the performances were a celebration of one of Britpop’...

After season two’s mortifying ending, the charming hit comedy is back for the last time … with sex parties, extreme cringe and a final answer to the central will-they-won’t-theyThere are cliffhangers, and then there’s whatever happened at the end of Colin from Accounts’ second season. We had, by that point, witnessed protagonists Ashley and Gordon’s unconventional love story evolve from bizarre meet-cute – key stages: boob-flashing, car accident, injured dog – to soulmate-level relationship. ...

The anti-fascist consensus about our Nazi past is fundamental to German democracy. But that, shockingly, is being shatteredAs shock at the scale of the far right’s resounding state-election victory in Germany reverberated on Sunday, not everybody was unhappy.Seconds after the first exit polls from Saxony-Anhalt were revealed, Donald Trump posted the results on his Truth Social platform, seemingly delighted by the devastation of the centrist-conservative Christian Democrats (CDU) and the surge...

It was her very first film and it won her an Oscar. But can Callie Khouri now make it work on stage with songs? She talks about what made her write it – and how little has changed since‘I have a world-class case of beginner’s luck,” says Callie Khouri, who won an Oscar for her very first screenplay, Thelma & Louise. She also scored a hit with her first TV series, Nashville, which lasted six seasons. And at 68, she is taking on another first by penning a musical theatre version of Thelma &...

Les scores en compréhension de l’écrit et en mathématique des élèves de 15 ans n’ont jamais été aussi bas en France depuis 2000, comme dans les pays comparables. Parmi les raisons invoquées pour expliquer ce phénomène mondial, le rapport aux apprentissages, la place du numérique, les effets durables de la crise du Covid-19 et le désinvestissement des parents. En France, les fortes inégalités sociales et de genre persistent.

Selon l’armée ukrainienne, l’armée russe a lancé une attaque massive de missiles et de drones visant principalement Kiev et son oblast ainsi que celui d’Odessa. Deux personnes ont été tuées et dix blessées, dont deux grièvement, dans la capitale ukrainienne, où des dizaines d’incendies sont signalés, selon le maire.

Les modalités de l’accord pétrolier conclu entre Washington et Caracas restent floues. La mainmise des Etats-Unis sur les réserves vénézuéliennes ne permettra pas de compenser dans l’immédiat les barils perdus au Moyen-Orient.

La start-up française d’intelligence artificielle, accusée par certains experts d’avoir abandonné la course face aux Américains et aux Chinois pour se développer dans les data centers et les services, assure ne pas avoir renoncé à produire des modèles de pointe. Elle signe sa plus grosse levée de fonds et voit Samsung entrer dans son capital.

L’ancien commandant de l’armée serbe en Bosnie-Herzégovine, condamné par la justice internationale pour génocide, crimes contre l’humanité et crimes de guerre lors des conflits dans l’ex-Yougoslavie dans les années 1990, et mort dans la prison de La Haye, a été enterré lundi dans la capitale serbe.

Mistral announced Tuesday that it had raised three billion euros ($3.5 billion) in what it described as the largest-ever European tech fundraising, valuing the French AI firm at over 21 billion euros.

Authorities in Nepal on Tuesday said that rescuers are focusing on three hydropower project tunnels where they believe dozens of workers could be trapped. The announcement came two weeks after ​a devastating ‌flood killed that hundreds and left thousands missing in the Himalayan country and in ⁠neighbouring China's Tibet region.

As the Champions League resumes, Real Madrid are hosting Inter Milan. Speaking at a press conference, Kylian Mbappé believes he has every chance of winning the Ballon d’Or.

Canada's counter-tariffs on billions of dollars in US products took effect Tuesday, as a trade war between the two countries heated up. Ottawa's pushback comes weeks after US President Donald Trump imposed 50-percent tariffs on a similar value of Canadian products, over what Washington deemed as "discriminatory treatment" against US alcohol, automobile and dairy industries.

DER SPIEGEL has learned that a large number of fraudsters have obtained German citizenship by claiming to be the descendants of Jews persecuted by the Nazis. The real families are furious.

The numbers of Chinese cars on European roads is skyrocketing as carmakers from the People’s Republic rush to build factories in the EU. Germany’s traditional brands are struggling to respond.

Anthropic founder Amodei and OpenAI CEO Altman once worked together to build a Super AI. Now, they are competing to be first. And that race is proving dangerous.

Brussels is concerned about the rising number of migrants reaching Crete - and is allowing itself to be blackmailed by the notorious Haftar family in eastern Libya, as DER SPIEGEL reporting has found.

Pornographic material is strictly forbidden in the People's Republic of China. Yet demand is high nonetheless. Many of the films are produced in Taiwan – but performers do their best to conceal that fact.

Vor allem im Lesen und in Mathematik gehen die Leistungen deutscher Schüler deutlich zurück. In den Naturwissenschaften übertreffen 14 Staaten Deutschland deutlich.

Jeder sollte mal eine asiatische Schule besuchen, empfiehlt der Koordinator der PISA-Studie, Andreas Schleicher. Im Interview spricht der Bildungsforscher über das Abschneiden Deutschlands und die Erfolgsrezepte der Spitzenreiter.

Die AfD gibt sich staatstragend. Sie betont, regieren zu wollen. Doch sie baut schon für den Fall des Scheiterns vor.

BSW-Vorsitzende bekräftigt Wunsch nach überparteilichem Ministerpräsidenten +++ Sepp Müller will CDU-Vorsitzender in Sachsen-Anhalt werden +++ Merz: Sind zutiefst schockiert +++ alle Entwicklungen im Liveblog

Die Polit-Talkshow nach einem historischen Wahlabend geriet zum Rätselraten, was der Wahlsieger in Sachsen-Anhalt mit seinem Triumph anfängt. Der AfD-Gast in der Runde trug nicht wirklich zur Aufklärung bei.

Police are on the hunt for thieves who stole three paintings from the Renoir Museum on the French Riviera in an overnight heist. A fourth stolen work was abandoned as they fled.

The influential global study shows a downward trend in students' performances. Germany is faring worse than ever.

A team from a small southwestern German town of just 7,000 inhabitants made history by sealing promotion to become the 59th club to play in the Bundesliga. Elversberg has got off to a memorable start.

Spain's football federation are set to join a handful of clubs in paying for female players to freeze their eggs during their careers. While players have pushed for the move, there are welfare concerns too.

After the Eiffel Tower was closed amid a staff strike over alleged discrimination, Hindu group BAPS issued an apology, but maintained that no one was denied access. DW has more.