AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- Microsoft ResearchresearchFrom synthetic enterprise data evaluations to real Microsoft Copilot AI confidence
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation unde…
- LessWrongresearchNeutral Isn’t Independent: LLM @-invocation
Consider a situation where multiple news outlets publish similar stories. A reader may model these as independent, and thus strongly update on the information presented. But imagine that the text of the story makes clear…
- arXiv cs.AIresearchLRMoE: Demand-Side Load Re-Calibration for Efficient MoE Training on Memory-Constrained Nodes
arXiv:2610.37720v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models offer scalable capacity for Web applications, but uneven routing creates computation and communication bottlenecks. Existing placemen…
- arXiv cs.AIresearchAmortized Localized Posterior Inference for Model Calibration with Application to an Ocean Turbulence Closure
arXiv:2610.37731v1 Announce Type: new Abstract: Model discrepancy may prevent a single calibration parameter from reproducing a physical response across the context domain. In addition, uncertainties in observations and…
- arXiv cs.AIresearchThinkJev: One Thought, Every Budget for Calibrated Typed Decisions
arXiv:2610.37732v1 Announce Type: new Abstract: Many uses of language models end in a typed decision: a choice among a closed set of options, whose probabilities code can act on. Reading those probabilities from one forw…
- arXiv cs.AIresearchOpenFrontiers: A Collection of Open Research Problems and a Benchmark for Scientific Rediscovery
arXiv:2610.37739v1 Announce Type: new Abstract: Large language models (LLMs) have shown increasing promise in research-level problem solving, yet a comprehensive collection of such problems is still missing, and evaluati…
- arXiv cs.AIresearchWhat Constitutes Food Similarity? Visual Representations and Retrieval in Indian Cuisine
arXiv:2610.37867v1 Announce Type: new Abstract: Food similarity underlies retrieval, recommendation, substitution, and other food computing tasks, yet food representations are typically evaluated by identity preservation…
- arXiv cs.AIresearchVerification Learning Theory: A Process Model of Checking and Retention in AI-Assisted Judgment
arXiv:2610.37875v1 Announce Type: new Abstract: Accurate AI assistance can improve immediate judgments while reducing opportunities to practise the operations needed for independent performance. Verification Learning The…
- arXiv cs.AIresearchThe Anatomy of Socio-Demographics in Pluralistic Offensiveness Modeling: When and Where It Helps, and the Role of Reasoning
arXiv:2610.37896v1 Announce Type: new Abstract: Subjective judgments such as offensiveness often vary substantially across individuals, motivating pluralistic modeling approaches that incorporate annotators' socio-demogr…
- arXiv cs.AIresearchBeyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
arXiv:2610.37906v1 Announce Type: new Abstract: Spiking reservoir computing combines the training efficiency of fixed recurrent reservoirs with the energy efficiency of event-driven inference, where computation is trigge…
- arXiv cs.AIresearchVerifiedLab: Harnessing Knowns for Unknowns
arXiv:2610.37923v1 Announce Type: new Abstract: Across human history, knowledge has undergone several transitions, from orality to writing and then to digital archives. At each transition, humans established new conventi…
- arXiv cs.AIresearchUnderstanding Large Language Models as Numerical Optimizers
arXiv:2610.37932v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as potential tools for numerical optimization. Despite promising results, their intrinsic optimization capabilities and limitation…
- arXiv cs.AIresearchGAUSS: A Workload-Aware Analytical and Monte-Carlo Simulator for LLM Inference Serving
arXiv:2610.37989v1 Announce Type: new Abstract: Large language model (LLM) inference has become an operational workload that fleets must provision, monitor, and bill against latency service-level objectives (SLOs). A sin…
- arXiv cs.AIresearchAlgorithmic Bias from the Perspectives of Healthcare Professionals
arXiv:2610.38006v1 Announce Type: new Abstract: This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems. Based on the quantitative data and qu…
- arXiv cs.AIresearchAssessing Language Models for Scientific Applications: Inertial Confinement Fusion as a Use Case
arXiv:2610.38024v1 Announce Type: new Abstract: Advancing language models for specialized scientific applications requires evaluations of scientific fluency, physical reasoning, and quantitative analyses. Using inertial…
- arXiv cs.AIresearchPromptSense: Sentiment-Aware Mental Health Chatbot with Dynamic Prompting
arXiv:2610.38044v1 Announce Type: new Abstract: Current Large Language Models (LLMs)-based mental health chatbots often lack sufficient empathy, contextual awareness, and safety mechanisms, potentially leading to ineffec…
- arXiv cs.AIresearchEvaluating Causal Reasoning in LLMs: A Case Study in the Challenges of Procedural Generation
arXiv:2610.38100v1 Announce Type: new Abstract: Large language models (LLMs) appear to represent and reason about a large range of phenomena. In particular, recent studies have examined whether LLMs can accurately reason…
- arXiv cs.AIresearchAI-Driven Digital Twin Framework for Warehouse Logistics Automation Optimization
arXiv:2610.38101v1 Announce Type: new Abstract: In recent years, warehouse logistics optimization has increasingly focused on intelligent, data-driven systems to enhance operational efficiency. Conventional static produc…
- arXiv cs.AIresearchToo Hard, Too Easy, Just Right: Performance-Driven Challenge Adaptation in Virtual Reality Firefighter Training
arXiv:2610.38117v1 Announce Type: new Abstract: Effective firefighter training requires practice under dynamic and stressful emergency conditions, yet real-world live-fire exercises are costly, risky, and difficult to sc…
- arXiv cs.AIresearchPost-Training Large Language Models with LLMON
arXiv:2610.38120v1 Announce Type: new Abstract: Large Language Models (LLMs) treat all context tokens uniformly, lacking explicit separation between executable instructions and passive data. This leads to prompt injectio…
- arXiv cs.AIresearchDecompose, Don't Expand: Capability-Independent AI Systems by Construction
arXiv:2610.38144v1 Announce Type: new Abstract: A recurring design choice in building AI systems is whether, when a task is too hard for a model, to expand the model (make it larger, better-prompted, fine-tuned), or to d…
- arXiv cs.AIresearchBridgeRouter: Gain-Aware Instance Routing over Cross-Modal Bridge Portfolios
arXiv:2610.38152v1 Announce Type: new Abstract: Lightweight representation bridges make pretrained, task-adapted EEG foundation models executable on other biosignal modalities without retraining their backbones. However,…
- arXiv cs.AIresearchPrototype-Guided Dynamic Domain Modulation and a Large-Scale Multi-SKU Benchmark for Shampoo Bottle Surface Defect Detection
arXiv:2610.38194v1 Announce Type: new Abstract: Industrial shampoo-bottle surface defect detection must operate across many stock keeping units (SKUs), where differences in bottle geometry, material, label layout, reflec…
- arXiv cs.AIresearchGAAC: Lossless KV Compression for Bandwidth-Efficient LLM Inference on Personal Devices
arXiv:2610.38210v1 Announce Type: new Abstract: Weight-only, lossy quantization substantially reduces the storage and memory requirements for serving large language models (LLMs), but the growing key-value (KV) cache rem…
- arXiv cs.AIresearchRubricon: Automated Rubric Generation and Refinement for LLM Evaluation and Training
arXiv:2610.38220v1 Announce Type: new Abstract: Rubrics enable reward assignment on tasks without verifiable answers, but are expensive to manually produce from scratch. We present Rubricon, a pipeline that generates dis…
- arXiv cs.AIresearchVerification-Guided Retrosynthesis: Reaction Feedback and Evidence Timing
arXiv:2610.38245v1 Announce Type: new Abstract: Retrosynthesis planning seeks synthesis routes from purchasable starting materials to a target molecule. Search over predicted reactions can connect a target to available m…
- arXiv cs.AIresearchInner-Learning: From Hand-Coded Beliefs to Declarative Knowledge in Trick-Taking Games
arXiv:2610.38304v1 Announce Type: new Abstract: We present a declarative approach to belief-state modeling in trick-taking card games. Starting from a state-of-the-art Skat player, we automatically extract its hand-coded…
- arXiv cs.AIresearchGame-Theoretic Foundations for Undiscounted Bisimulation Metrics
arXiv:2610.38313v1 Announce Type: new Abstract: Bisimulation metrics offer a principled notion of task-relevant state similarity in reinforcement learning, but existing constructions and methods are largely confined to d…
- arXiv cs.AIresearchCHORD: Cross-Model Hallucination Detection via Relational Graph Discrimination
arXiv:2610.38314v1 Announce Type: new Abstract: Hallucination detection is critical for deploying large language models (LLMs) in real-world applications. Due to strong empirical performance, internal representation-base…
- arXiv cs.AIresearchCan LLMs Faithfully Solve Ontology Engineering Tasks? A Mechanistic Interpretability Study
arXiv:2610.38326v1 Announce Type: new Abstract: Ontological knowledge underpins large language model (LLM) performance on knowledge-intensive tasks. However, existing evaluations of LLMs' ontological understanding largel…
- arXiv cs.AIresearchEncode Once, Answer Many: Internalizing Context via Parametric Flow
arXiv:2610.38356v1 Announce Type: new Abstract: Large language models are typically adapted to a task either by placing knowledge in the input context, which keeps it external and re-encodes it on every call, or by fine-…
- arXiv cs.AIresearchCompute Has Shape: Self-Morphing the Internal Computation of Frozen LLMs
arXiv:2610.38382v1 Announce Type: new Abstract: Test-time scaling improves large language models through additional computation, but how to adapt the topology of internal computation to individual inputs remains underexp…
- arXiv cs.AIresearchDES-JEPA: Learning a Shared Vocabulary for High-Dimensional Discrete Event Sequences
arXiv:2610.38445v1 Announce Type: new Abstract: Temporal foundation models such as Chronos and TimesFM generalize across domains through a shared numerical observation space. In contrast, discrete event sequences (DESs),…
- arXiv cs.AIresearchAccelerating Nonlinear MPC by Behavior Cloning with Separated Timescales: Application to Nuclear Reactor Load-Following
arXiv:2610.38496v1 Announce Type: new Abstract: Behavior Cloning (BC) of expert controllers for multiscale dynamical systems is challenging: state variables evolving at widely separated timescales induce highly nonlinear…
- arXiv cs.AIresearchValue Probes: Learned Value Functions for Beam-Search Red Teaming
arXiv:2610.38526v1 Announce Type: new Abstract: Automated red-team auditing of language models is an important way to evaluate safety-relevant behaviors. These audits implicitly search a tree of possible conversation pat…
- arXiv cs.AIresearchFrom Leniency to Suspicion: How an Open Post-Training Recipe Changes Whom LLM Fact-Checkers Believe
arXiv:2610.38532v1 Announce Type: new Abstract: LLMs increasingly fact-check online content with the poster's identity in view. However, it remains unclear which post-training changes how much a model's truth judgement d…
- arXiv cs.AIresearchPT$^3$: Prototype-Guided Self-Supervised Pretraining for Generalizable mmWave Human Point Cloud Representation
arXiv:2610.38551v1 Announce Type: new Abstract: Multi-source millimeter-wave (mmWave) observations offer an opportunity to learn human representations reusable across sensing tasks. However, sparse detections and multipa…
- arXiv cs.AIresearchCo-Evolving Policy and Rubric via Capability Awareness for Open-Ended Generation
arXiv:2610.38566v1 Announce Type: new Abstract: Rubric-based reinforcement learning (RL) offers interpretable, fine-grained supervision for aligning large language models (LLMs) on open-ended generation tasks. However, s…
- arXiv cs.AIresearchA-RSI: Adaptive Task Refresh for Zero-Data Multimodal Self-Improvement
arXiv:2610.38568v1 Announce Type: new Abstract: Recursive self-improvement requires models not only to acquire useful training experience, but also to decide when their current experience has ceased to be useful. Existin…
- arXiv cs.AIresearch"Close enough?" An investigation into multiplication errors in LLMs
arXiv:2610.38634v1 Announce Type: new Abstract: Large language models (LLMs) frequently fail at multi-digit arithmetic, but the underlying mechanisms governing these failures remain poorly understood. While recent work d…
- arXiv cs.AIresearchWeaken to Strengthen: Weakening-Induced On-Policy Self-Distillation for Large Reasoning Models
arXiv:2610.38681v1 Announce Type: new Abstract: Self-distillation offers a way to improve reasoning models when a suitable external teacher is unavailable. However, common approaches rely on privileged information to con…
- arXiv cs.AIresearchDeogen: Automatic Benchmark Generation for Reasoning over Policies
arXiv:2610.38687v1 Announce Type: new Abstract: Language models are increasingly being deployed in regulated settings, where a model must apply given rules to the facts of a situation to determine a verdict. Benchmarking…
- arXiv cs.AIresearchFrom Grind to Grasp
arXiv:2610.38728v1 Announce Type: new Abstract: Discussions of complexity, knowledge and intelligence often overlook the work involved. For example, outputs generated by short programs have low algorithmic complexity but…
- arXiv cs.AIresearchLeaving, Staying, or Living There? Duration Commonsense Reasoning with Human-LLM Co-annotations
arXiv:2610.38755v1 Announce Type: new Abstract: Gardening in the backyard implies living there, while checking into an Airbnb more likely means staying for a few days. Such duration judgments are important for understand…
- arXiv cs.AIresearchLearning to Reason from Reference Samples Alone: Reinforced Adversarial Learning for Modern LLM Post-Training
arXiv:2610.38851v2 Announce Type: replace Abstract: In many settings where LLM post-training is desirable, high-quality answers are recognizable but difficult to score with explicit rewards. Reinforcement learning with v…
- arXiv cs.AIresearchDungeons & Dragons Encounter Analysis with Semi-Random Simulation in Foundry VTT
arXiv:2610.38975v1 Announce Type: new Abstract: Dungeons & Dragons (D&D) is a tabletop roleplaying game (TTRPG) in which a group of players, guided by a Game Master, roleplay a fantasy adventure with simulated combat and…
- arXiv cs.AIresearchContext Compaction for World Models
arXiv:2610.38980v1 Announce Type: new Abstract: World models let observers explore and interact with generated worlds. Recent work shows that when observers revisit a region, current models often fail to regenerate it co…
- arXiv cs.AIresearchSyntactic Segmentation and Collage Generation for Videogame Levels with Perceptual Distance
arXiv:2610.38987v1 Announce Type: new Abstract: In procedural videogame level design, many existing techniques combine hand-authored level chunks. Some existing analysis techniques also rely on a higher-level graph struc…
- arXiv cs.AIresearchFormal Specifications with Data-Driven Signal Analysis
arXiv:2610.39007v1 Announce Type: new Abstract: Developing analog and hybrid systems requires substantial domain knowledge that is hard to articulate in a formal specification; without additional effort, this domain know…
- arXiv cs.AIresearchWhen Should AI Decide, Defer, and Deviate? Responsible Automation for Deceased Donor Kidney Allocation
arXiv:2610.39045v1 Announce Type: new Abstract: We ask when an AI trained on historical decisions should be allowed to recommend decisions, defer to human experts, or in other cases, flag concerning patterns in data and…