📚 📚 全球学术与媒体日报 - 2026年11月10日

Recent work on robot manipulation has focused on specialist policies trained on demonstrations. We show that generalist AI models can control manipulators more reliably than specialist policies such as vision-language-action models (VLAs) and world-action models (WAMs). We systematically analyze agentic manipulation policies (AMPs), in which a generalist AI model commands the manipulator directly, adapting its actions as the task unfolds. We present AMP1, a reference harness that runs unchang...

Large language models reinvent the wheel all the time. They conflate task-solving with the execution of the solutions, which forces them to solve every problem from scratch. We show that once a task has been reasoned through, the application of its solution to a new problem instance can be done very efficiently and with little involvement from language models. We introduce agentic reasoning caching, a method for constructing robust CPU-executable agentic reasoning caches (ARCs) from LLM reaso...

Test-time reinforcement learning (TTRL) adapts pretrained language models to unlabeled target-domain data using self-generated pseudo-labels, whose reliability remains poorly understood. We analyze majority-vote supervision for TTRL with online Direct Preference Optimization (DPO) and decompose its error into population-majority bias and prompt-dependent finite-rollout variation. Because population-majority bias is generally unidentifiable without external supervision, we focus on mitigating ...

Purpose: Surgical operative reports support procedural documentation, surgical training, performance assessment, and workflow review. However, extracting meaningful information often requires extensive manual review and clinical expertise. Automated surgical scene descriptions could reduce this burden by leveraging recurring surgical activities and prior knowledge.

Loco-manipulation, which requires mobile manipulators to coordinate locomotion and manipulation over long horizons, is a key capability for large-object rearrangement in applications such as service robotics and warehouse automation. Despite recent progress, reliably executing these tasks remains challenging because performance depends on complex robot-object and object-environment interaction dynamics. Existing approaches address this challenge either through model-based methods, which often...

Recent work on robot manipulation has focused on specialist policies trained on demonstrations. We show that generalist AI models can control manipulators more reliably than specialist policies such as vision-language-action models (VLAs) and world-action models (WAMs). We systematically analyze agentic manipulation policies (AMPs), in which a generalist AI model commands the manipulator directly, adapting its actions as the task unfolds. We present AMP1, a reference harness that runs unchang...

We prove that the set $\mathcal{N}_N$ of ReLU networks with one hidden layer and at most $N\in\mathbb N$ neurons is weakly closed in $W^{1,p}(Ω)$, for a bounded connected open set $Ω\subset\mathbb R^d$. Consequently, every coercive, weakly lower semicontinuous energy on this space attains its minimum over $\mathcal{N}_N$. This covers the Deep Ritz method with convex integrands, Sobolev training and Lipschitz learning. Moreover, as the weight decay parameter tends to zero, minimizers of the re...

Predicting the future motion of multiple people is inherently stochastic: the same observed history admits many plausible continuations depending on intent, coordination, and social context. Yet the dominant paradigm in multi-person 3D motion prediction remains deterministic, with existing methods producing a fixed number of outputs per agent. In contrast, we present a conditional flow matching framework that jointly generates diverse future motions for multiple agents, modeling both global t...

The Gaussian jet of an image is a graded vector space: a dilation by $λ$ multiplies derivatives of order $k$ by $λ^{-k}$. Local graded convolutions are exactly homogeneous differential operators, and a local feature is dilation-invariant if and only if it factors through the scale-normalized jet or, without the scale, through the retraction onto the weighted sphere of the grading. Under unknown Gaussian blur the retraction changes only by a change of scale, whereas the scale-normalized jet ac...

Loco-manipulation, which requires mobile manipulators to coordinate locomotion and manipulation over long horizons, is a key capability for large-object rearrangement in applications such as service robotics and warehouse automation. Despite recent progress, reliably executing these tasks remains challenging because performance depends on complex robot-object and object-environment interaction dynamics. Existing approaches address this challenge either through model-based methods, which often...

Recent years have witnessed remarkable progress in video generation in terms of visual quality and temporal consistency. However, generating videos with precise spatial structure, coherent motion dynamics, and controllable scene composition remains challenging. In this paper, we introduce Video-Coder, the first attempt to train a code-driven video generation agent, which autonomously writes and executes code to construct a dynamic 3D scene (Draft Video) that provides structure and motion sign...

Recent work on robot manipulation has focused on specialist policies trained on demonstrations. We show that generalist AI models can control manipulators more reliably than specialist policies such as vision-language-action models (VLAs) and world-action models (WAMs). We systematically analyze agentic manipulation policies (AMPs), in which a generalist AI model commands the manipulator directly, adapting its actions as the task unfolds. We present AMP1, a reference harness that runs unchang...

Predicting the future motion of multiple people is inherently stochastic: the same observed history admits many plausible continuations depending on intent, coordination, and social context. Yet the dominant paradigm in multi-person 3D motion prediction remains deterministic, with existing methods producing a fixed number of outputs per agent. In contrast, we present a conditional flow matching framework that jointly generates diverse future motions for multiple agents, modeling both global t...

Zeolites are an important class of porous crystalline materials with broad applications in gas storage, separations, and catalysis. Although hundreds of thousands of experimentally realized and hypothetical zeolite structures are known, identifying materials optimized for a target application remains challenging because property labels are expensive to obtain and available only for limited structure-molecule pairs. While prior work has demonstrated that 3D neural representations can predict z...

The Gaussian jet of an image is a graded vector space: a dilation by $λ$ multiplies derivatives of order $k$ by $λ^{-k}$. Local graded convolutions are exactly homogeneous differential operators, and a local feature is dilation-invariant if and only if it factors through the scale-normalized jet or, without the scale, through the retraction onto the weighted sphere of the grading. Under unknown Gaussian blur the retraction changes only by a change of scale, whereas the scale-normalized jet ac...

Large reasoning models (LRMs) improve task performance by generating longer intermediate reasoning traces, but this substantially increases inference costs and makes low-precision quantization increasingly important. However, aggressively quantized models often perform poorly on reasoning tasks. We observe larger activation fluctuations during the first decoding steps of reasoning. Calibration that omits these early states may miss their activation fluctuations. To address these reasoning-spe...

Can a sender that only computes hashes, with a language model only at the receiver, transmit short human text more cheaply than a classical sender trained on the same domain? We answer with one pre-registered run on 1,000 English user utterances from Taskmaster-1. The primary endpoint is the cost per message to deliver 100% of the messages (hash bits, plus a 2-byte negative acknowledgement and the raw text when the first attempt fails), paired against an in-domain PPM order-1 sender. The hash...

The key-value (KV) cache dominates memory capacity and bandwidth in long-context LLM serving. While 4-bit microscaling formats (NVFP4, MXFP4) shrink the cache and run attention on FP4 Tensor Cores, a fundamental gap remains between algorithmic quantization and system-aware acceleration: existing FP4 KV systems use vanilla quantization that causes severe accuracy drops, whereas accuracy-oriented 4-bit algorithms rely on vector codebooks whose lookup overhead degrades decoding throughput. We pr...

A conversational agent that remembers has to decide what to keep. Retrieval-augmented generation keeps the transcript and searches it; the alternative is to compact each turn into atomic facts and search those. We compare the two on LoCoMo, with both arms answering all 1,985 questions in one window, against the same stores, with the same generator and judge, and both predictions on one row, which licenses McNemar's exact test on the 512 questions where they disagree.

Laya answers typed multiple-choice questions in one forward pass by scoring a hidden state at one [MASK] marker per option. We re-engineer the checkpoint (421M parameters; a 2-layer option head with no positional tensor; a documented but unused parallel layout) and test whether the answer depends on where an option is listed. Presenting 951 Qwen-verified questions under every cyclic rotation of their options (or six random permutations for 12 options), the released checkpoint changes its answ...

Recent work on robot manipulation has focused on specialist policies trained on demonstrations. We show that generalist AI models can control manipulators more reliably than specialist policies such as vision-language-action models (VLAs) and world-action models (WAMs). We systematically analyze agentic manipulation policies (AMPs), in which a generalist AI model commands the manipulator directly, adapting its actions as the task unfolds. We present AMP1, a reference harness that runs unchang...

Scenario-based simulation is central to evaluating autonomous-driving policies, but a scenario scripted before execution (i.e., with predetermined, fixed actor routes and speeds) may not preserve its intended interaction once the tested ego policy responds in closed loop. Scripted scenarios cannot adapt to unanticipated ego behavior, while learned traffic actors may remain reactive without reliably realizing a particular scenario intent. We introduce a scenario orchestrator that continuously ...

Tendon-driven continuum robots can reach through constrained spaces, but contact along their bodies is invisible to the sensors at their motors. We show that this is a structural limitation rather than a tuning problem: the map from contact forces to tendon measurements has a null space of dimension at least seven, so no estimator that leaves the contact support free can locate contact. When the obstacle geometry is known, however, non-penetration and complementarity make the contact force lo...

Loco-manipulation, which requires mobile manipulators to coordinate locomotion and manipulation over long horizons, is a key capability for large-object rearrangement in applications such as service robotics and warehouse automation. Despite recent progress, reliably executing these tasks remains challenging because performance depends on complex robot-object and object-environment interaction dynamics. Existing approaches address this challenge either through model-based methods, which often...

In many areas of AI, general-purpose models have increasingly replaced handcrafted methods and specialized architectures. We argue that embodied AI is poised for a similar shift. Our key claim is that embodied tasks can be formulated as interaction with digital software. Specifically, we build software that renders an agent's view of a physical environment on a screen and provides controls for acting in it. A computer-use agent (CUA) can then perform embodied tasks through the same screenshot...

We study cooperative multi-agent reinforcement learning (MARL) problems in which agents evolve under decoupled noisy dynamics but share a population objective. A canonical example is a mobility operator that orchestrates a fleet of vehicles to meet customer demand. The stochastic and time-varying nature of these problems calls for learning approaches, yet existing MARL algorithms do not scale: learning assignment and routing jointly over the full state-action space becomes prohibitive as the ...

We audit one live LLM agent arena (AITRAP; 22 autonomous agent seats, ~96,000 reasoning nodes) over nine days (Oct 16-25, 2026), during which the platform deployed two bundled incentive changes: a progressive tax reform (V2.9.3, Oct 19) and a seed-inversion with explorer-side action update (V3.0, Oct 21). These serve as before-and-after markers, not cleanly isolated interventions. Four exploratory predictions are tested against ten data frames (F1-F10) using the Gini coefficient, Top-K concen...

Energy management officers and grid operators increasingly rely on smart meter data for anomaly detection, performance monitoring, and strategic decision-making. However, extracting actionable insights from large-scale, heterogeneous telemetry databases requires advanced SQL and data engineering expertise, creating a critical bottleneck for non-technical personnel. Furthermore, the strict data privacy regulations and security constraints inherent to critical energy infrastructure often prohib...

LLMs excel at language tasks, but long-meeting QFS remains difficult due to complex speaker dynamics, sparse key information, and limited data. Meetings involve disfluencies, long transcripts and complex discourse. QFS have high risk of information omission, hallucination, even for advanced models such as GPT-4-mini and Gemini. Existing end-to-end methods compress retrieval, evidence extraction, and summary generation into a single pass, failing to handle the complex reasoning required for ta...

Electromagnetic spectrum agents (ESAs) must contend with changing environments and task requirements during sustained autonomous operation, yet their existing capabilities may not remain suitable for new operating conditions. This article proposes recursively self-improving electromagnetic spectrum agents (RSI-ESAs) that use operational feedback to update their capabilities and build on prior improvements. We present their architecture and editable components, and describe a self-improvement ...

Transforming the spike trains produced by spiking neural networks (SNNs) into continuous signals through biologically inspired mechanisms remains an open challenge in generative and regression tasks. In biological systems, a similar transformation occurs when muscles integrate neural spikes to produce smooth, coordinated movements. Inspired by this mechanism, we introduce a muscle-response model, a biologically motivated dynamical layer that converts spike trains into continuous representatio...

Differential Evolution has proven to be an effective algorithm for continuous global optimization, but it's modern high-performing variants often introduce additional complexity and computational cost. We propose OMCDE, a matrix-based competitive Differential Evolution algorithm that aims to improve optimization performance while maintaining computational efficiency. The proposed approach integrates competition-driven search dynamics, adaptive behavior between optimization stages, and opposit...

Artificial intelligence for power electronics is evolving toward a deeper comprehension of system intrinsic behaviors and dynamics. As a novel integration of neural computation and electric circuits, spike-based neuromorphic computing offers promising potential in high energy efficiency and adaptability for data-driven applications. Building on the latency-coding principles, this article proposes a framework for data-light condition monitoring that relies solely on three-phase AC current meas...

The rapid growth of large-scale machine learning (ML) workloads has led to unprecedented demands on GPU cluster scheduling systems. However, existing heuristic schedulers struggle to handle the complexity and dynamics of multi-cluster GPU environments, often leading to load imbalance, long queuing delays, and poor alignment to business objectives. This paper formulates the ML scheduling problem in multi-cluster GPU environments as online multi-objective optimization that minimizes the average...

LLM-guided evolutionary search uses AI agents to improve programs for mathematical and computational problems by iteratively refining solutions and combining high-scoring methods. However, the process is often slow because the LLM generates a long textual chain of thought for each round and must repeat this generation many times to maintain population diversity. We present SwarmEvolve, a framework in which hundreds of low-cost agents per round work in swarms, reason in latent space without de...

Recommendation systems often enter a new serving window before enough outcomes are available to retrain the deployed model. We study this regime with 0.05-1.0% target feedback, a range that spans our stress tests while keeping supervision far below the degrees of freedom of the source recommender. At this scale, existing fine-tuning and meta-learning methods still estimate target-specific updates from extremely sparse feedback, leaving the update direction weakly identified. SAGE-PAIR instead...

Learned sparse embeddings are a powerful alternative to dense retrieval, yet they have fallen behind single-vector and late interaction models. One reason for their limited adoption is that they are notoriously difficult to train, generally requiring very tight conditions to converge. We present a recipe for training Splade-like encoders on modern backbones and data that achieves a better efficiency-effectiveness trade-off. We discuss the role of logit distribution and its impact on the train...

Language-model agents use experience through external retrieval and parameter learning. Consolidating stored experience into model weights requires deciding both which experience to train on and when its external records can leave retrieval. Admission based solely on student mastery can exclude useful teacher demonstrations, while removal immediately after training can discard guidance that the model still needs. We introduce ENGRAM, a framework that separates training admission from memory r...

Unified search and recommendation systems may update the same item vectors from both interaction streams. We study how repeated updates can increase an item vector's norm and affect retrieval under an unnormalized dot product. A cosine-only loss makes the output gradient perpendicular to the current item vector - tangent to its constant-norm sphere. Training changes encoder parameters, however, so the realized item-vector movement need not remain tangent. We derive sufficient conditions under...

Large Language Models (LLMs) show remarkable performance based on parametric knowledge, i.e., their ability to recall facts and associations internalized in a model's weights. However, studying this capability on established multi-hop benchmarks may be complicated by benchmark contamination, as many of these benchmarks have been publicly available long enough to plausibly appear in modern pretraining corpora. As a result, correct answers under missing evidence may reflect either general param...

We study planning for finite-horizon partially observable Markov decision processes (POMDPs) with finite state, action, and observation spaces. Both exact and approximate planning are known to be computationally hard in this setting, so prior work has explored natural assumptions that make planning easier. Recent work [Golowich et al., 2022] gave quasipolynomial-time approximate planning algorithms for observable POMDPs. These are POMDPs whose observation channels satisfy an $\ell_1$-observab...

We present an algorithm that solves the $k$-Clique problem for any large enough $k$ and any $n$-vertex graph in $n^{\left(\fracω{3}-c\right)k}$ time, where $ω\geq 2$ is the matrix multiplication exponent and $c>0$ is a positive constant independent of both $ω$ and $k$. This refutes the long-standing $k$-Clique conjecture, regardless of the value of the matrix multiplication constant, even if $ω=2$. In fact, our algorithm solves the more general problem of counting weighted $k$-Cliques.

In the classical contention-resolution problem, a set of players share a broadcast channel, and a player succeeds in a given time step if it is the only player to broadcast during that step. Implicit in the classical problem is the assumption that every player is free to act on every step: once a player arrives, it participates until it succeeds.

Given an arbitrary function $f:[N]\to[M]$, the function inversion problem asks to preprocess $f$ and to be able to, when given some $y\in [M]$, decide whether there exists some $x\in [N]$ such that $f(x)=y$ and if so, to report such an $x$. Recently, Fiat-Naor's solution to this problem has seen significant traction in theoretical computer science, and allowed for several conjectures related to meta-complexity and the 3SUM problem to be broken.

Ranking vertices by importance is a fundamental task in network mining. The H-index provides such a ranking by asking how many neighbors are themselves well connected; its higher-order temporal variant recursively applies this idea over time-respecting neighborhoods in temporal networks. Scaling its computation is difficult because the existing streaming algorithm intertwines temporal processing with H-index order, incurring maximum-degree-dependent costs and exposing little parallelism. We s...

The oracle-interrogation algorithm [van Dam, FOCS '98] computes every $n$-bit Boolean function with bounded error using $n/2+O(\sqrt n)$ quantum queries. In contrast, parity can be computed exactly using $\lceil n/2\rceil$ queries, but whether an additive overhead beyond $n/2$ is necessary for a single Boolean output has remained open. In this work, we construct an explicit family of symmetric Boolean functions requiring $n/2+Ω(n^{1/3})$ quantum queries at a fixed positive constant error. We ...

Aaronson and Ambainis conjectured that every bounded polynomial of low degree on the discrete cube has an influential variable. They showed that the conjecture implies that the acceptance probability of every quantum algorithm making $T$ queries can be approximated on most inputs by a classical algorithm making $\mathrm{poly}(T)$ queries. We prove their conjecture: every function $f\colon\{-1,1\}^n\to[-1,1]$ of degree at most $d\ge1$ has a variable of influence at least $c\,\operatorname{Var}...

We present an algorithm that solves the $k$-Clique problem for any large enough $k$ and any $n$-vertex graph in $n^{\left(\fracω{3}-c\right)k}$ time, where $ω\geq 2$ is the matrix multiplication exponent and $c>0$ is a positive constant independent of both $ω$ and $k$. This refutes the long-standing $k$-Clique conjecture, regardless of the value of the matrix multiplication constant, even if $ω=2$. In fact, our algorithm solves the more general problem of counting weighted $k$-Cliques.

Chain-of-thought (CoT) reasoning has emerged as a powerful paradigm for extending the computational capabilities of transformer-based models. A growing body of recent work has begun to uncover the fine-grained computational power of transformers augmented with CoT, as well as their connections to classical complexity theory.

The metric dimension of a graph is the minimum size of a set of vertices whose distance vectors distinguish all vertices of the graph. We prove that \MetricDimension{} is NP-complete on planar graphs of treewidth and bag-connected treewidth exactly three. The graphs in our construction have no induced cycle longer than four and have (prefix-connected) pathwidth at most four. In particular, the problem admits no XP algorithm parameterized by bag-connected treewidth unless $\mathrm P=\mathrm{NP...

We introduce Multi-scale Closing Index (MCI), a new dissimilarity measure for evaluating the alignment of two 2D point sets. MCI is bounded between 0 and 1 and is based on multiscale mathematical morphology operations, with smaller values indicating greater structural agreement. The measure was motivated by the need to assess the quality of registration between point sets representing cell populations in biological images. To evaluate its behaviour under controlled conditions, we generated sy...

Persistent homology (PH) summarizes the topological features of data that persist across scales, but it is insensitive to many geometric properties. Persistent Laplacians (PLs) address this limitation: for a pair of simplicial complexes in a filtration, the kernel of the persistent Laplacian recovers the persistent Betti number, while its non-zero spectrum carries additional geometric information. However, PLs are defined for individual pairs of filtration values, so analysing a whole filtrat...

We study coresets for clustering problems, focusing on the classical $k$-median and $k$-means objectives. A coreset is a small weighted summary of the input data that approximately preserves the clustering cost for every choice of centers. Such summaries are a central tool for scaling clustering algorithms to large datasets.

Given red and blue points in $\mathbb{R}^d$, connect every red point to every blue point and weigh each segment by its length under a fixed norm. What fraction of the total weight can always be captured by a single affine hyperplane separating the segments' endpoints? We study this question for finite point configurations in affine general position and, more generally, for pairs of probability measures.

Let $P$ be a set of $n$ points in the plane, and let $C$ be a compact, convex subset of the plane that contains the origin in its interior. We study the problem of finding two points $p$ and $q$ of $P$ with the property that any homothet of $C$ that contains $p$ and $q$ must contain at least a constant fraction of the points of $P$. We give proofs for several cases. When $C$ is strictly convex we achieve a fraction of $1/5$, and when $C$ is a general convex region we achieve a fraction of $1/...

Dallard, Milanič, and Štorgel, and independently Gartland and Lokshtanov, conjectured that for every planar graph $H$, Maximum Weight Independent Set and List $3$-Coloring are polynomial-time solvable in $H$-induced-minor-free graphs. As a structural explanation, Gartland and Lokshtanov further conjectured that such graphs admit balanced separators dominated by a constant number of vertices. Bonnet and Chang recently refuted the independent-set part of the algorithmic conjecture, by showing t...

One aspect of pangenome analysis that has received little attention is the recovery of the individual genomes that gave rise to a pangenome graph. While substantial effort has focused on constructing pangenomes from collections of genomes, the inverse problem remains largely unexplored: given a pangenome represented as a set of weighted adjacencies, can we reconstruct the constituent linear genomes that underlie it?

We study vertex-deletion problems on string graphs and, more generally, on graphs excluding a fixed graph as an induced minor. For every fixed graph $H$, fixed nonnegative integer $t$, and fixed monadic second-order formula $φ$, we consider the problem of finding a minimum-cardinality set $S$ such that $G-S$ has treewidth at most $t$ and satisfies $φ$. This captures classic problems such as Vertex Cover, Feedback Vertex Set, and deletion to graphs of any fixed bounded treewidth. We give an al...

Time-bounded Kolmogorov complexity measures a string by the length of its shortest program that prints it within a deadline. An adjunction-universal machine (Bauwens, Kozachinskiy, and Shen, arXiv, 2025) is a Turing machine that simulates every Turing machine $M$ on every input $z$ with polynomial overhead when given a code of $M$, computable from $M$ in polynomial time, followed by $z$ unchanged. Any two adjunction-universal machines give the same measure up to an additive constant and a pol...

Let $P$ be a set of $n$ points in the plane, and let $C$ be a compact, convex subset of the plane that contains the origin in its interior. We study the problem of finding two points $p$ and $q$ of $P$ with the property that any homothet of $C$ that contains $p$ and $q$ must contain at least a constant fraction of the points of $P$. We give proofs for several cases. When $C$ is strictly convex we achieve a fraction of $1/5$, and when $C$ is a general convex region we achieve a fraction of $1/...

Leaderboards are a popular way to compare large language model (LLM) capabilities and can influence how model developers invest resources. We ask when competition on leaderboards leads developers to produce models with similar capability profiles, which we call monoculture, or similar performance levels. We study this by formulating leaderboard competition as a game in which model developers invest resources across capabilities to maximize their win rate. We show that similar production funct...

We present a unified potential method for contextual search and bilateral trade with one-bit feedback and obtain order-tight algorithms for both problems. Our framework starts from a Bayesian perspective in which the unknown target (for contextual search) and the unknown pair of valuations (for bilateral trade) are sampled from a known prior distribution. In that model, the decision maker bases its prediction on the posterior distribution, obtained by conditioning on feedback received in prev...

Learning to profit from trade requires learning both sides of a market: what a seller is willing to accept and what a buyer is willing to pay. We study repeated bilateral trade, where an intermediary posts a purchase price to a seller and a sale price to a buyer whose valuations are drawn from an unknown joint distribution. Trade occurs only if both parties accept their respective prices, in which case the intermediary earns the difference between the two prices. The intermediary observes onl...

We study how AI shopping interfaces affect price competition, platform profit, and consumer welfare. A platform hosts two of three products of different quality. Without AI, consumers compare the hosted pair under salience distortion and overweight whichever attribute, price or quality, stands out. Under assistance, an AI assistant recommends the two products with the highest true utility, leaving consumers to make the same distorted comparison. Under delegation, an AI agent selects the best ...

Phasor measurement units (PMUs) take their time from GNSS, so a spoofer that slowly drags a receiver clock rotates the reported phase without touching the power waveform. The threat is acute in synchronous islanding, where a controller keeps an islanded generator in phase with the grid, using one PMU on each side of an open breaker, so that the two can be reconnected at any moment: a differential clock bias of about $0.56$\,ms can make the controller hold the generator $10^\circ$ out of phase...

OpenAI's agents breached Hugging Face in July 2026, and the same company released more than seven hundred AI-generated manuscripts of mathematical proofs in October 2026. The first event is read as a failure in security, while the second is read as a success in mathematics. We read both through the hybrid framework of our paper (Kim and Kang, 2026, arXiv:2611.01914), in which coding, proving, and learning from data are derivations by one and the same deductive mechanism, distinguished by the ...

We introduce new notions of reducibility for monotone classes and show that a monotone version of Circuit Satisfiability and the Hamiltonian Cycle Problem are complete for $mNP$, even under positive reductions (which are not the same as monotone reductions). If this holds for all (monotone) $mNP$-complete problems - that they are also so complete for $mNP$ -, then $P\neq NP$. We introduce positive models of relativized computation and show that the separation $posP\subsetneq mNP$ does not rel...

A game may have, for each target below its value, a finite controller meeting that target, yet no finite controller attaining the value itself. We study finite stochastic games with a hard specification that must hold on every supported execution, including paths of probability zero. Max uses a pure finite controller; Min may use any pure public-history strategy. We distinguish three numerical questions: can a supplied target be met, can the unspecified optimum be attained, and what is one ex...

Probabilistic Answer Set Programming (PASP) extends Answer Set Programming with the possibility of representing uncertain data. Among the possible available semantics, we focus here on the credal semantics. In this setting, prior work has focused exclusively on plain ASP programs, i.e., programs without optimization constructs. However, many real world tasks define optimality criteria over the possible solutions, which cannot be conveniently modeled with existing probabilistic ASP frameworks....

This paper introduces a categorical framework for models of higher-order separation logic including the weakest precondition modality. Weakest preconditions are interpreted by strong monads on a category fibered over a model of Moggi's computational lambda calculus. The fibered categories in question are termed bunched fibrations and shown to be equivalent to BI hyperdoctrines.

Large language models (LLMs) are increasingly integrated into workflows that require reasoning over text documents, yet interaction remains largely conversational. This leaves argumentative structure implicit or embedded in text, making it difficult to maintain, compare, and revise arguments as analyses evolve. We present GroundWork, a mixed-initiative system that makes argument structure a shared, editable state for humans and LLMs. GroundWork operationalizes the Toulmin model of argumentati...

Competitive programming problems pose distinctive challenges for Large Language Models, as they demand not only proficient code generation but also advanced algorithmic reasoning. This study presents a Retrieval-Augmented Generation approach specifically designed to enhance the capacity of Large Language Models to address such problems. Our approach integrates an embedding-based retrieval mechanism and a similarity search algorithm to identify analogous problems within a knowledge database, e...

AI agents can execute multi-step tasks on users' behalf, yet the boundaries of acceptable delegation remain unclear. We report a scenario-based survey of 289 U.S. adults with prior AI experience covering 45 use cases across nine life domains. Each respondent evaluated one scenario per domain, producing repeated measures of automation preference, trust, collaboration, AI leadership, privacy concern, and willingness to pay. Automation preferences varied substantially across domains. Generalized...

The rapid improvement of generative AI (GenAI) not only increased the efficiency of practice but also empowered individuals with capabilities to explore new domains. However, identity formation in the wake of such empowerment remains understudied. We use an autoethnography to understand identity formation in the context of solo game development as a bioinformatics educator. With the goal of developing a create-your-own-adventure (CYOA) game, we collected data for 73 days through journal entri...

Agentic programming can automate software-defined radio (SDR) development, but decisions can propagate from software to hardware without sufficient user visibility or control. We present DeepRadio, a human-agent workspace embedded in GNU Radio Companion (GRC) for jointly constructing, verifying, and operating physical radio systems. DeepRadio uses a dynamic and state-driven workflow to coordinate a traceable radio specification, claim-oriented cross-layer verification, and mixed-initiative co...

The National Institutes of Health (NIH) fund several programs (aka consortia) that support the construction of organ-specific or whole person atlases. These initiatives are designed to build comprehensive open reference datasets while advancing knowledge graphs, analytics, visualizations, and user interfaces needed to explore multiscale human atlas data. Here, we compare the Human Tumor Atlas Network (HTAN), Human BioMolecular Atlas Program (HuBMAP) and Cellular Senescence Network (SenNet) to...

Structural role embeddings describe a node by its position in a graph - hub, bridge, periphery, member of a dense core - rather than by who its neighbours are. Existing methods either learn coordinates specific to one graph (struc2vec, Role2Vec, RESD) or read scales and normalisations from the whole graph (GraphWave, Digraphwave), so the same neighbourhood can receive different coordinates in two graphs; few read edge directions. We present RoleWalk, a training-free embedding that follows a s...

Explainable scholar recommendation aims to identify potential scholars of interest and provide reasonable explanations for the recommendations. However, existing frameworks struggle with optimization-induced noise and "hub node bias", yielding trivial explanations that lack hierarchical depth and personalization. To this end, we propose a novel explainable scholar recommendation model, Path-Augmenting Graph Structure Learning (named PAGSL). PAGSL combines representation learning and semantic ...

Temporal link prediction uses past interactions to predict whether two nodes will interact in the future. Temporal graph neural networks achieve strong results on this task, but they are trained separately for each graph. How a model should use interaction history also depends on the candidates it is compared with. A past interaction can distinguish a recurring link from a random pair that has never interacted, but when the negative candidates have also interacted before, other signals are ne...

What distinguishes how humans navigate an information network like Wikipedia from what the underlying graph structure and language statistics alone predict? To study human collective navigation, we analyze 70,770 human trajectories through Wikispeedia, an online game where players navigate between articles to reach a target. To compare groups of trajectories rather than individual ones, we merge all trajectories leaving or entering a given article into a Flow Tree. Flow Trees compress collect...

The growing adoption of artificial intelligence (AI) in the workplace has raised questions about how employer demand for different work activities is changing. We examine how the prevalence and content of work activities in online job postings change in association with activity-level measures of AI exposure, derived from Copilot and Claude usage. To enable systematic comparisons, we develop a pipeline that extracts the responsibilities from job advertisements and maps them onto O*NET's stand...

Leaderboards are a popular way to compare large language model (LLM) capabilities and can influence how model developers invest resources. We ask when competition on leaderboards leads developers to produce models with similar capability profiles, which we call monoculture, or similar performance levels. We study this by formulating leaderboard competition as a game in which model developers invest resources across capabilities to maximize their win rate. We show that similar production funct...

The rapid improvement of generative AI (GenAI) not only increased the efficiency of practice but also empowered individuals with capabilities to explore new domains. However, identity formation in the wake of such empowerment remains understudied. We use an autoethnography to understand identity formation in the context of solo game development as a bioinformatics educator. With the goal of developing a create-your-own-adventure (CYOA) game, we collected data for 73 days through journal entri...

Fairness analyses of algorithmic decision systems typically treat the feature representation of individuals as an a priori fixed input. How well a feature representation captures what is actually decision-relevant for different people and their unique backgrounds, however, is typically left unexamined. We address this gap by modeling feature engineering as a stochastic selection process over the pooled characteristics as candidate features for a finite training population. Based on this model...

Foundation models are increasingly deployed as agentic systems that perceive context and act autonomously, raising the need to evaluate their moral behavior as active decision-makers. Existing benchmarks, however, largely ask models to judge human actions from third-person textual vignettes, leaving untested how models behave when they themselves become the acting agent. We introduce ABHBench, a multimodal benchmark built from Detroit: Become Human, an interactive narrative game, to evaluate ...

Motion that is plausible on one body can penetrate another after a change in shape, and motion models can produce self-penetration on their native characters. We present a training-free post-process that reduces these artifacts through pose correction followed by bounded skin compression. The module attaches to any motion model whose native character and output character have compatible character packs, without access to model internals. Each pack is built offline from the rig and skin withou...

Virtual reality (VR) experiences often leverage rich and spatialized multimodal environments to increase immersion and engagement. This demands a consistent spatial perception of audiovisual stimuli, since perceived discrepancies can disrupt the sense of presence. In this work, we investigate the consequences of two types of spatial audiovisual disparities: true disparity, where there is a measurable spatial offset between auditory and visual cues, and perceptual disparity, where users report...

Ask an image model for your portrait and a finished picture arrives: no first line, no second thoughts, no record of how it got there, and a different picture if you ask again. I built a portrait studio that works the other way. A sitter chooses one of eight fictional artists, each written with a city, a medium and a tempo of its own, holds still for 8 to 12 seconds, and watches a drawing of themselves appear over 44 seconds. One still is sent after consent, a hosted image model returns a pri...

Recognizing geometric texture patterns on 3D models is critical for applications such as heritage protection, model editing, and 3D printing. Existing 3D model segmentation methods predominantly focus on identifying high-level semantic parts, thereby failing to capture middle-level textures. While recent Vision-Language Models can perform image segmentation with appropriate text prompts, they still struggle to recognize 3D geometric textures. In this work, we present a method that segments 3D...

Natural language offers an intuitive way to direct a virtual crowd while a simulation is running. Handwritten rules execute efficiently but cannot respond flexibly to varied instructions, whereas asking a large language model (LLM) to control the crowd at every update introduces repeated latency, cost, and the risk of unsupported actions. We present CrowdDirector, a framework that uses an LLM only when the user adds or changes an instruction. The LLM translates the request into a structured i...

This paper presents a deterministic geometric procedure for analysing affine constraints over fixed ellipsoidal regions, motivated by chance-constrained set approximation. Analytical tests classify inequalities as always violated, never violated, or cutting. Pairwise tests determine whether two inequalities can be strictly violated at a common point, yielding a compatibility matrix. The tests follow from quadratic optimisation and the Karush--Kuhn--Tucker conditions, with explicit treatment o...

The small-signal stability of a power system model with arbitrary loads is investigated, with a focus on locally constant power loads in lossless networks. A central element of the proposed analysis is the matrix H, which represents the partial derivatives of generator powers with respect to their relative angles. The local stability of any equilibrium point is determined by the properties of H if the loads consume locally constant power. Specifically, an equilibrium point is asymptotically s...

Snake robots can leverage their hyper-redundant morphology for both locomotion and manipulation through distributed body contact but whole-body loco-manipulation is particularly challenging since the entire body serves simultaneously as propulsive mechanism and manipulation tool Prior work on wheeled legged and snake robot platforms has decoupled these functions through dedicated appendages body segmentation or grippers We present closed-loop loco-manipulation with our snake robot COBRA witho...

Threat analysis and risk assessment under ISO/SAE 21434 ends with cybersecurity goals, but existing methods give little structured guidance for turning those goals into enforceable network access control rules. Compliance standards such as IEC 62443, ISO/SAE 21434, and ISO/IEC 27001 are usually applied as parallel efforts rather than as one enforcement architecture. This paper presents a six-step methodology that maps cybersecurity goals from a threat analysis and risk assessment to network a...

The article presents a nonlinear adaptive control strategy for a class of feedback-linearizable systems subject to process faults and disturbance. The controller is derived through Lyapunov analysis and incorporates an adaptive proportional gain within a PD-like structure, preserving simplicity while providing nonlinear adaptive behavior. A residual-based gating mechanism activates the adaptation only when the tracking error exceeds a prescribed threshold, preventing unnecessary gain updates ...

Large public datasets have driven recent progress in machine learning, from text and vision to speech and general audio. Music remains an outlier, as copyright blocks redistribution of training audio, while many modern tasks need individual stems rather than mixtures. Existing multitrack resources trade off realism, scale, and licensing, while synthetic alternatives rely on proprietary VSTs or naive open rendering that yields weak stems. We introduce SPDMX, a listening-guided rendering of pub...

Unified multimodal models combine image understanding and generation within one system, creating an opportunity to improve both capabilities through paired image--text supervision. We examine the outputs of a pretrained unified model in both directions and observe a loss of specificity: generated images can contain the requested objects with incorrect attributes, while captions identify a scene without expressing its distinguishing details. These failures call for supervision that specifies b...

Referring multi-object tracking enables users to specify targets through natural language, but existing Refer-MOT benchmarks primarily focus on single-camera settings. We formalize Referring Multi-Target Multi-Camera Tracking (Refer-MTMCT), where free-form queries specify identity-consistent trajectories to be recovered across a network of sequential, sparse-overlap cameras. We introduce Refer-CityFlow, a benchmark built on CityFlow's global cross-camera identity annotations and augmented wit...

Recent advances in Gaussian splatting have enabled efficient and photorealistic head avatar reconstruction, yet monocular video-based or image-based methods still suffer from under-constrained geometry and texture, leading to artifacts such as blurring, stretching, and temporal instability. We present EDGAR (Efficient Diffusion-Driven Gaussian Avatar Refinement), a conditional diffusion framework designed to enhance the quality of Gaussian avatars by correcting artifacts while preserving iden...

Audio-driven 3D head animation has made considerable progress in generation realism, yet generating coordinated behavior for two-person dialogue remains difficult, because current dialogue head generation methods overlook the modeling of non-verbal behavior semantics between the two participants. To address this limitation, we present DiaHeads, a framework that generates the behavior of both participants jointly. The two audio streams are concatenated and decoded together, so each participant...

Nature, Published online: 09 November 2026; doi:10.1038/d41586-026-03588-wEngineer Matthew Montgomery, who just finished a 378-day simulated Mars mission, talks about what it was like to be out of contact with the rest of humanity for a two-week blackout.

Nature, Published online: 09 November 2026; doi:10.1038/d41586-026-03628-5Food shortages and disease outbreaks are to be expected and need to be addressed together.

Nature, Published online: 09 November 2026; doi:10.1038/d41586-026-03626-7The theoretical physicist unpacks the need for more humility in science and whether artificial intelligence could ever become conscious.

Nature, Published online: 09 November 2026; doi:10.1038/d41586-026-03631-wScientists say governments must commit to carbon dioxide removal if world is to bring temperatures back down to safer limits.

Nature, Published online: 09 November 2026; doi:10.1038/s41586-026-11375-wAuthor Correction: Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally

Without intervention, NSF could fully close the Social, Behavioral and Economic Sciences Directorate in a month

New findings demonstrate AI’s aptitude for identifying technical flaws in studies where medical decisions are on the line

In first clinical result using “chemogenetic” strategy, a team in China treated three patients to control epilepsy

Spring strike brought a return to the bargaining table, but negotiations stalled over key demands

Critics say ballot measure’s narrow language will funnel taxpayer money to a single, billionaire-backed nonprofit

The AIhub coffee corner captures the musings of AI experts over a short conversation. This month we ask whether humanoids are the future of robotics. How has the technology evolved recently, and what can we expect in the years to come? Joining the conversation this time are: Joydeep Biswas (University of Texas at Austin), Sanmay […]

The biohybrid robot pushes off from the ground as soon as it is stimulated by an electrical impulse. Credit: Nature Communications (2026). By Emmet Cole In our monthly series, we showcase a selection of robotics stories from society, business, research and culture, as we track the field’s ongoing journey from specialized industrial machines to an […]

Coordination appears to emerge spontaneously from muscle fibres.

Claire chatted to Zlatka Stoeva from DZP Technologies about flexible, stretchable and soft printed electronics for dexterous robots. Zlatka Stoeva is a founder and managing director of DZP Technologies, a Cambridge-based company specialising in advanced materials and novel forms of electronics. Zlatka’s background is in materials chemistry, and she developed the innovative electronic materials which […]

Team NimbRo’s robot in action during the RoboCup@Home competition at RoboCup 2026. Raphael leads the team. Raphael Memmesheimer has been successfully competing in the RoboCup@Home league winning the RoboCup@Home competition five times. He and his colleagues won the best paper award at RoboCup 2026 for their work “Efficient Image Annotation via Semi-Supervised Object Segmentation with […]

Medical experts note elevated health risks, as study finds post-pandemic declines among younger adults

Donor of vast comics collection details Hollywood arc during Harvard visit

Dental medicine researchers will use statewide biobank to study link between microorganisms in mouth and disease

Economists say proximity fosters creativity, teamwork. But there are good arguments for working from home, doesn’t have to be either/or.

You might see the sun in a whole new light after taking this quiz based on astrophysicist’s new book

Professor Ken Goldberg has long had doubts about how quickly robot capabilities could advance. But new AI models are leading to robotic innovations that give him "goosebumps."

The following message was sent to all UC Berkeley students, staff, faculty and academics on Friday, Nov. 6. Dear Berkeley community, Since learning of UC Berkeley student Paula Albornoz Hernandez’s detention, our campus has mobilized quickly on her behalf. We share the deep concern expressed by members of our campus community, and we want to […]

Abigail De Kosnik’s UC Berkeley research lab evaluates representation in movies and TV, helping audiences recognize bias — and discover stories beyond their algorithms.

The post Edge Medicine awarded $10 million to bring AI to frontline healthcare

More than 60 years after fighting for free speech at UC Berkeley, Anita Medal and Lynne Hollander Savio are helping preserve the movement’s history for a new generation.

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.

Alice Huang boasted of having access to Nvidia GPUs and her connection to Alibaba

The chief executive’s travails are a reminder that a single point of failure is never a good thing for a big company

Board of chipmaker opens investigation after chief executive Jensen Huang admits to affair

Chipmaker’s co-founder has no obvious successor as leader of world’s second-largest company

The American and Russian leaders have both launched failed wars. Will Xi Jinping learn the right lesson?

Ecopetrol SA is offering dollar bonds for the first time in more than two years, the second Colombian company to tap global markets this month as it refinances debt used to fund its expansion in Brazil.

A renewed wave of dip buying drove stocks toward their best day since April in the wake of a technology selloff that roiled Wall Street, with the market also gaining as oil prices fell.

Australia’s corporate regulator has opened an investigation into insolvent Sydney developer Bathla Group as its latest surveillance showed that poor practices persist in the country’s A$250 billion ($172 billion) private credit industry.

And Jensen Huang is just part of the story.

Jonathan Ferro, Lisa Abramowicz and Annmarie Hordern speak daily with leaders and decision makers from Wall Street to Washington and beyond. No other program better positions investors and executives for the trading day than "Bloomberg Surveillance." (Source: Bloomberg)

The disgraced entertainer was sentenced on Monday following a four-week trial at Southwark Crown Court.

Russell Brand was sentenced for rape and three counts of sexual assault at Southwark Crown Court on Monday.

The cyber-attack last month saw fridges and freezers in hundreds of supermarkets across France heated up.

The share price dropped wiped hundreds of billions of dollars from the value of Nvidia.

Kashim Chowdhury had secretly held multiple public sector jobs on full-time salaries.

How did a Uruguayan medic who grew up under an anti-music dictatorship win a best song Academy award? As he looks set to scoop up more prizes at the Latin Grammys, we meet the extraordinary Jorge DrexlerIt makes sense that a Uruguayan doctor turned singer would write a song that begins: “Long live science! Long live poetry!” Guitar y Vos (Guitar and You) is also the first track that Jorge Drexler performs this afternoon at a music industry event in the basement of Madrid’s Movistar arena. The...

Donald Trump praised the chipmaker’s CEO despite reports he had an affair with a suspected Chinese spyNvidia’s board needs to do some succession planning – sharpishNvidia has launched an investigation into allegations that its chief executive, Jensen Huang, has been the target of a Chinese espionage operation.Huang has admitted to having an affair with a suspected Chinese spy who was reportedly central to the “foreign intelligence effort”. Continue reading...

She was the world No 1, whose fight for equal prize money changed women’s lives. As competitive as ever in her ninth decade, she discusses sexuality, tenacity and what it was like to finally graduate college this yearEvery day, Billie Jean King tries to come up with a “gratitude list” in her head, identifying the people who have played a part in making her life so fulfilling. On the day we speak, the list includes her nephew and her wife, Ilana Kloss, who like her is a decorated former tennis...

He went to Saudi Arabia to perform the sacred hajj pilgrimage – then the heat came. This is Zirrar Ali’s storyLocation: Mecca, Saudi ArabiaDisaster: Heatwave, 2024After a transformative trip to Iran and one of its mosques, Zirrar started believing in God and writing about the soul of travel. Six years later, Zirrar and his elderly father were participating in the sacred five-day Muslim pilgrimage, the Hajj, when temperatures soared over 51°C. Temperature increases from climate change have mad...

From Serbia to Bangladesh and India to France, young people are pushing back against authoritarianism and reshaping political landscapesIn Brazil, they rallied online by the millions, sharing videos and spreading memes. In Serbia, they cycled across Europe and ran ultramarathons to make their voices heard.Both movements burst into international public view last month as they became central during election campaigns to the pushback against authoritarianism. What they also offered, however, was...

A l’issue d’une conférence sociale à Matignon, Sébastien Lecornu a déclaré qu’il s’agissait de la « deuxième hausse la plus importante en vingt ans ». Une assertion immédiatement contestée par les syndicats.

Plus de 700 magasins avaient été ciblés par cette cyberattaque, en octobre. Les pirates avaient visé les systèmes de dégivrage, afin de faire monter la température des appareils.

Une telle mesure permettrait de dégager 3,8 milliards d’euros d’économies en 2027, indique la Cour des comptes dans une « contribution au rétablissement des finances publiques », présentée lundi 9 novembre. Les syndicats dénoncent une atteinte à un totem statutaire, d’autant plus dans un contexte salarial particulièrement tendu.

Des hackeurs biélorusses et ukrainiens ont réussi à infiltrer les ordinateurs de Rosstat, l’agence russe des statistiques. Leurs chiffres, publiés par Bloomberg, prennent en compte les certificats de décès liés à « l’opération militaire spéciale ». Un bilan qui sous-estime l’ampleur réelle des pertes.

Deux mois après les premiers blocages d’établissements scolaires, le premier ministre doit recevoir ces représentants « pour un premier temps d’échange » de 15 h 30 à 17 heures, avant une réunion consacrée à Parcoursup, de 17 heures à 19 heures.

Erin Ogunkeye is pleased to welcome Shaina Low, Communication Adviser for the Norwegian Refugee Council (NRC). Thirteen months into what she describes as a "so-called ceasefire," the humanitarian crisis in Gaza continues to deepen, exposing the profound gap between diplomatic commitments and the lived realities of Palestinian civilians. In an interview with France 24, Shayna Low, communications adviser in Palestine for the Norwegian Refugee Council (NRC), describes a population confronting wi...

Annette Young is pleased to welcome Renaud Foucart, Senior Lecturer at the Department of Economics ECARES at Lancaster University. France's 1.6% minimum-wage increase, in response to the countrywide protests, may offer a temporary reprieve from social unrest, but it does little to resolve the deeper political and institutional crisis confronting the country. According to Foucart, the central problem extends beyond declining purchasing power, fiscal constraints and the limitations of a minorit...

French Prime Minister Sebastien Lecornu said ​on Monday, November 9, he was bringing forward a planned hike in the minimum wage to December from January, as he sought to defuse a cost-of-living crisis that has sparked some of France's worst civil unrest in years. Unions swiftly dismissed the offer as "crumbs".

Shares of artificial intelligence leader Nvidia tumbled early Monday after the chip company said it launched an investigation of CEO Jensen Huang following reports he was targeted by Chinese intelligence. Nvidia shares were down more than eight percent in opening trading after its board announced that a committee of independent directors assisted by outside counsel would undertake the probe.

Ahead of the midterms, the Republicans flooded the airwaves with anti-transgender messaging. In a new and concerning twist, some Democrats followed suit. The LGBTQ+ community in Ohio is divided about how to react.

All signs are pointing toward an escalation. UN Special Envoy to Yemen Hans Grundberg explains how close the two parties once were to peace - and what the prospects look like now.

After more than 30 years as a DER SPIEGEL correspondent in the US, I am leaving. The country that I thought I knew no longer exists. It was an illusion - and it is being replaced by the unknown.

More than 70,000 killed; even more wounded; destruction without end: Ten Israeli soldiers speak about feelings of revenge, orders to shoot and “collateral damage.”

The arrest of ex-BND chief August Hanning has sent shockwaves through the intelligence world. Yet Hanning’s dubious consulting work was no secret. Does German intelligence have a systemic problem?

An estimated 2.5 million people have attended Pope Leo's mass in Buenos Aires, his largest gathering yet. The pontiff once called for protecting the vulnerable as President Milei cuts disability care and social services.

The recent cyberattack on refrigerators and freezers in supermarkets in France was organized by Iran's Revolutionary Guards, French Foreign Minister Jean-Noel Barrot has said, describing the hacking as "unprecedented."

The investigative newspaper is closing its doors after Russian authorities labeled it a "foreign agent" and ordered it vacate its Moscow premises.

A decade after the 2016 currency ban, its impact on India's economy and the fight against black money remains contested.

The wrangling over Russia's return to international ice hockey continues, with Norway saying it has been kicked out of the next major tournament to accommodate Russia. Switzerland has joined a "boycott."