AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchVerified, not generated: expert-verified AI study materials and the distribution of learning gains in a university course
arXiv:2610.07097v1 Announce Type: new Abstract: Experimental studies of generative AI in education mostly report average effects, yet field evidence shows that AI can narrow attainment gaps or widen them. We argue that t…
- arXiv cs.AIresearchSim-to-Real Transfer of Vision-Language Navigation in Continuous Environments Using an Ackermann-Steered Mobile Robot
arXiv:2610.07192v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) enables robots to navigate through environments using natural language instructions, making human-robot interaction intuitive. Traditional…
- arXiv cs.AIresearchEnergy-Conditioned Noise Schedule and Whitening for Spectral Diffusion
arXiv:2610.07206v1 Announce Type: new Abstract: This paper introduces an energy-adaptive noise scheduling and whitening strategy for transform-domain diffusion models. Existing spectral diffusion methods account for the…
- arXiv cs.AIresearchCascadia: Resident 975B MoE Inference on Eleven AI PCs
arXiv:2610.07219v1 Announce Type: new Abstract: Mixture-of-experts models make nearly trillion-parameter capacity accessible with sparse per-token computation, provided that the serving system can distribute the weights…
- arXiv cs.AIresearchSPECTRUM: Proximal Spectral Modulation for Looped Self-Distillation
arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distillation, a self-evolut…
- arXiv cs.AIresearchDoes the Model Use the Feature? Separating Steering from Mechanism in LLMs
arXiv:2610.07270v1 Announce Type: new Abstract: Internal features in LLMs are often interpreted as mechanisms when they track a concept and their manipulation changes a related behavior. Yet steering can push a feature f…
- arXiv cs.AIresearchRule-Based Languages for Neurosymbolic AI
arXiv:2610.07313v1 Announce Type: new Abstract: Logic programming is increasingly used as the symbolic component of neurosymbolic AI systems. We survey the main rule-based languages in this setting, namely Datalog, answe…
- arXiv cs.AIresearchRationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding
arXiv:2610.07342v1 Announce Type: new Abstract: On-policy reinforcement learning has become a central paradigm for improving the reasoning abilities of large language models. However, its effectiveness is often limited b…
- arXiv cs.AIresearchTrajectory-Retrieval Speculative Decoding: When Does a Model's Own History Help?
arXiv:2610.07350v1 Announce Type: new Abstract: Long chain-of-thought reasoning increases sequential decoding cost while creating a growing history of potentially reusable continuations. We investigate when this history…
- arXiv cs.AIresearchEvaluating Escalation Signals for LLM Routing: Targets, Controls, and Five Ways to Fool Yourself
arXiv:2610.07354v1 Announce Type: new Abstract: Deciding when to escalate a query from a small language model to a larger one requires a cheap signal that predicts, before the large model is called, whether escalating wo…
- arXiv cs.AIresearchDefense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced Sycophancy
arXiv:2610.07403v1 Announce Type: new Abstract: Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-induced sycophancy,…
- arXiv cs.AIresearch2d-fet-bench: from spatial reasoning to fet design on flakes
arXiv:2610.07423v1 Announce Type: new Abstract: Field-effect transistor (FET) layouts on exfoliated two-dimensional flakes are typically drawn by hand for each flake, placing contacts and gates to match its position and…
- arXiv cs.AIresearchAdaptive Gait Biofeedback With Participant-Held-Out Modeling and Participant-Specific Updating in Chronic Ankle Instability
arXiv:2610.07428v2 Announce Type: replace Abstract: Adaptive gait biofeedback may support repeated practice in chronic ankle instability, but its evaluation must address model performance and human response. We evaluated…
- arXiv cs.AIresearchWhen Does AI Supervision Help? A Role-Aware Study of Network Fraud Decision Management with Blockchain Auditability
arXiv:2610.07434v1 Announce Type: new Abstract: When does a second artificial intelligence (AI) component improve a primary network-fraud decision rather than add operational burden? We study this question through a role…
- arXiv cs.AIresearchCOMPASS: Finding Where Reasoning Lives in Language Models
arXiv:2610.07469v2 Announce Type: replace Abstract: Explicitly eliciting reasoning substantially improves LLM performance. Existing approaches require a predefined characterization of reasoning, whether through CoT promp…
- arXiv cs.AIresearchIn With the Old: Enhancing 'Classical' Document Automation with Generative AI
arXiv:2610.07480v1 Announce Type: new Abstract: Software-based legal assistance systems have leveraged many different forms of knowledge representation and reasoning. This article explores how document automation service…
- arXiv cs.AIresearchDoes Muon Need Fine-Grained Spectral Shaping?
arXiv:2610.07497v1 Announce Type: new Abstract: Muon combines current and past gradients into matrix momentum. For $M=U\Sigma V^\top$, the idealized polar update $Q=UV^\top$ gives every singular direction the same weight…
- arXiv cs.AIresearchMARS: Multi-resolution Adaptive Routing for Sequential Recommendation
arXiv:2610.07505v1 Announce Type: new Abstract: Long-history recommenders often compress each user's history into a compact, candidate-independent memory that is cached and reused to score large candidate pools. We show…
- arXiv cs.AIresearchFrom Local Evidence to Safety Verdicts: Causal Tracing in Vision-Language Models
arXiv:2610.07514v1 Announce Type: new Abstract: A vision-language model may need to combine an image with a prompt to recognize a safety risk that neither reveals alone. Where does this joint safety judgment become acces…
- arXiv cs.AIresearchA Systematic Investigation of Bias in Large Language Models for Advertising Relevance
arXiv:2610.07544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to judge how well an advertisement matches a query, but the fairness of these judgments has received limited attention. W…
- arXiv cs.AIresearchNavigating Route Latent Space for Synthesizable Molecular Design
arXiv:2610.07560v1 Announce Type: new Abstract: Goal-directed molecular design has advanced rapidly, yet a substantial proportion of designed molecules remain difficult to synthesize in practice, limiting their real-worl…
- arXiv cs.AIresearchLOGIC: An LLM Benchmark for Intent-Grounded Change Impact in Aerospace Electrical Systems
arXiv:2610.07580v1 Announce Type: new Abstract: Aerospace electrical-design revisions can contain multiple genuine changes, although an engineering request may authorize only a subset. Propagating every detected differen…
- arXiv cs.AIresearchRepresentation Bias, Correction Transfer, and Resolution Sensitivity in Three-Dimensional Mitochondrial Morphometry
arXiv:2610.07582v1 Announce Type: new Abstract: Quantitative imaging pipelines can produce precise but systematically different measurements of the same object. We present an empirical reliability assessment of three-dim…
- arXiv cs.AIresearchLSC-DPO: Learning-Signal-Controlled Direct Preference Optimization
arXiv:2610.07592v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) has become a standard reward-model-free approach for aligning language models with preference data. However, as the scaled preference m…
- arXiv cs.AIresearchBeyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding
arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where generated temporal inte…
- arXiv cs.AIresearchVALSE: Vertical Adaptive Layer Skipping for Efficient Inference in Large Language Models
arXiv:2610.07606v1 Announce Type: new Abstract: This paper establishes a theoretical framework for vertical adaptive layer skipping, proving three foundational results: (i) an Expected FLOPs formula (theorem 2) giving a…
- arXiv cs.AIresearchExplore, Then Commit: Measurement-Efficient Scientific Law Discovery with Language Models
arXiv:2610.07620v1 Announce Type: new Abstract: Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol in which a large lan…
- arXiv cs.AIresearchLearning to Outgrow a Theory: Experimental Discovery Beyond the Initial Hypothesis Space
arXiv:2610.07627v1 Announce Type: new Abstract: Scientific discovery systems typically optimize experiments within a fixed hypothesis space. This creates a failure mode when all available candidates omit the same missing…
- arXiv cs.AIresearchMeasuring climate backlash in Twitter and Reddit archives: Lexical definitions, recorded responses and participant turnover
arXiv:2610.07634v1 Announce Type: new Abstract: Social media archives are often used to study resistance to climate action, but words, response counters and observed participants do not measure the same social process. W…
- arXiv cs.AIresearchLearning Explainable Representations of Complex Game-playing Strategies
arXiv:2610.07638v1 Announce Type: new Abstract: As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules to improve their pe…
- arXiv cs.AIresearchMatching Object or Relation? Tracing Abstract Reasoning Inside VLMs
arXiv:2610.07646v1 Announce Type: new Abstract: Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document this failure but cannot…
- arXiv cs.AIresearchMassive Activation Gating Channel in Large Language Models
arXiv:2610.07661v1 Announce Type: new Abstract: Massive activations, a phenomenon in which a small number of hidden channels exhibit exceptionally large magnitudes, are pervasive in large language models (LLMs). However,…
- arXiv cs.AIresearchBluffJAX: Adversarial Imperfect Information Games in JAX
arXiv:2610.07686v1 Announce Type: new Abstract: We introduce BluffJAX: an open-source suite of adversarial imperfect information games in JAX. We provide canonical implementations of games designed for high simulation th…
- arXiv cs.AIresearchOn the Boundary of Admission Gates: An Injected-Truth Study of Falsification-First Selection in Quantitative Strategy Research
arXiv:2610.07701v1 Announce Type: new Abstract: Strategy research conflates two problems: finding a profitable rule, and establishing that the finding is not search luck. The latter calls for admission gates -- statistic…
- arXiv cs.AIresearchEvidence Before Sampling: Interpretable Implicit Negative Candidate Discovery for Recommendation
arXiv:2610.07708v2 Announce Type: replace Abstract: Recommender systems learn from observed user-item interactions, but explicit negative feedback is often unavailable. Since deep learning models require negative signals…
- arXiv cs.AIresearchOTel: Open Telco AI Datasets, Benchmarks, and Models
arXiv:2610.07766v5 Announce Type: replace Abstract: We present Open Telco (OTel), an open telecom AI resource that releases derived telecom datasets for retrieval, reranking, instruction tuning, and safety/abstention, to…
- arXiv cs.AIresearchIllusory Pattern Perception Drives Spurious Inference in Large Language Models
arXiv:2610.07791v1 Announce Type: new Abstract: Illusory pattern perception is a well-documented human cognitive tendency to infer meaningful relationships in data that is actually random. Such a tendency, often describe…
- arXiv cs.AIresearchThin Evidence, Thick Priors: How Language Models Substitute Identity for Missing Financial Facts
arXiv:2610.07798v1 Announce Type: new Abstract: People increasingly ask large language models what to do with their money, yet seldom describe their finances in full. This paper asks what a model does with the gap. Holdi…
- arXiv cs.AIresearchThinkFuse: Trajectory-Aware Test-Time Fusion for Small Reasoning Models
arXiv:2610.07803v1 Announce Type: new Abstract: Small reasoning models (SRMs) have shown strong performance on complex reasoning tasks by generating extended chain-of-thought trajectories, but they often fail to recover…
- arXiv cs.AIresearchTextual Environmental Context and Spatial Graphs for LLM-Based Regional SST Forecasting
arXiv:2610.07895v1 Announce Type: new Abstract: Sea surface temperature (SST) forecasting depends on local temporal persistence, regional spatial dependence, and environmental conditions that evolve with the forecast dat…
- arXiv cs.AIresearchIsotropic Yet Undecodable: The Sequential Content-Sufficiency Gap in Latent-Predictive Text Representations
arXiv:2610.07906v1 Announce Type: new Abstract: We study sequential content sufficiency by investigating whether a representation retains the ordered target information available in its input. An information-theoretic de…
- arXiv cs.AIresearchContinuous Memory Machines
arXiv:2610.07907v1 Announce Type: new Abstract: Recurrent neural networks typically compress information into a single vector-valued recurrent state, forcing short-term computation and long-term retention to share the sa…
- arXiv cs.AIresearchLearning in Dreams, Winning in Reality: A Continuous Dyna Loop for a Ten-Hero MOBA
arXiv:2610.08033v1 Announce Type: new Abstract: World models are usually judged from the inside: by prediction loss, by the return a policy earns in imagination, or by how convincing their frames look. We judge one from…
- arXiv cs.AIresearchNatural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing
arXiv:2610.08095v1 Announce Type: new Abstract: Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advanced Text-to-SPARQL, yet on unfamiliar graphs they of…
- arXiv cs.AIresearchPartially Observable Zero-shot coordination by Predicting Intention of Partner
arXiv:2610.08142v1 Announce Type: new Abstract: Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous partner representations…
- arXiv cs.AIresearchWhich alloy composition,what process parameters? Inferring the recipe from optimized metallic microstructure and texture
arXiv:2610.08165v1 Announce Type: new Abstract: The mechanical properties of a metallic alloy are set by its microstructure and texture: the size and shape of its grains and the orientation of their crystals. That struct…
- arXiv cs.AIresearchLFHE: Local-First Heuristic Evolution for Bounded Local Topology Search in Decentralized Learning with Non-IID Data
arXiv:2610.08176v1 Announce Type: new Abstract: Decentralized learning is highly sensitive to communication topology under non-IID data. Adaptive peer-selection methods can exploit local model information, but broader pe…
- arXiv cs.AIresearchQuantum Entangled Multimodal Fusion Networks (QEMFN): Resource-Aware Hybrid Vision-Language Fusion via Trainable Entanglement
arXiv:2610.08216v1 Announce Type: new Abstract: Multimodal vision-language systems typically fuse image and text embeddings through classical operators such as concatenation, attention, bilinear pooling, or tensor intera…
- arXiv cs.AIresearchConfidence-Ordering Reversal under Contextual Priors in Neural Decoding
arXiv:2610.08229v1 Announce Type: new Abstract: Contextual priors improve neural-to-language decoding by reshaping candidate scores. However, confidence is read from the same reshaped scores, so the errors a prior leaves…
- arXiv cs.AIresearchOSFP4: Joint Optimization of Diagonal Smoothing and Block Scales for NVFP4 Quantization
arXiv:2610.08231v1 Announce Type: new Abstract: NVFP4 is an attractive datatype for large language model (LLM) inference, offering compact storage and native tensor-core acceleration. However, preserving accuracy using N…