AI news archive.
19,901 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis
arXiv:2610.28836v1 Announce Type: new Abstract: This study proposes a sketch-to-simulation system to solve handwritten circuit diagrams. The system converts raw images into a Simulation Program with Integrated Circuit Em…
- arXiv cs.AIresearchSpeedrunning Relational Foundation Model Pretraining
arXiv:2610.28855v1 Announce Type: new Abstract: Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception. Recipes are developed inside individual labs, repor…
- arXiv cs.AIresearchTo Manipulate or Not: Opinion Dynamics in LLM Interactions
arXiv:2610.28875v1 Announce Type: new Abstract: Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measur…
- arXiv cs.AIagentsFig: Automated Multiagent Behavior Elicitor
arXiv:2610.28891v2 Announce Type: replace Abstract: Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such…
- arXiv cs.AIagentsHidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication
arXiv:2610.28905v1 Announce Type: new Abstract: Diffusion language models form answers through a sequence of revisable continuous states, but multi-agent systems usually discard those states and make agents communicate o…
- arXiv cs.AIresearchDiffResearch: Accelerating Deep Research with Diffusion Language Models
arXiv:2610.28909v1 Announce Type: new Abstract: Deep research systems iteratively plan, gather evidence, synthesize, and revise, making end-to-end latency a key bottleneck for interactive use. Almost all production syste…
- arXiv cs.AIresearchSimply Logical -- The First Three Decades
arXiv:2610.28912v1 Announce Type: new Abstract: This paper charts the evolution of the Prolog textbook Simply Logical -- Intelligent Reasoning by Example from print with runnable programmes on a 3.5-inch diskette publish…
- arXiv cs.AIagentsD-Skill: Distilling Teacher Knowledge through Agent Skills
arXiv:2610.28914v1 Announce Type: new Abstract: Frontier language-model agents excel at complex tasks, but high inference costs make transferring their capabilities to smaller models essential. Traditional knowledge dist…
- arXiv cs.AIagentsBack Up Before You Regret: Measuring Backup Awareness and Automating Backup in Coding Agents
arXiv:2610.28934v1 Announce Type: new Abstract: Coding agents now complete tasks autonomously, modifying real-world state such as artifacts, software environments, and configurations along the way. Yet they show limited…
- arXiv cs.AIagentsSelf-Improving Agents with World Model Predictive Paths
arXiv:2610.28945v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly expected to interact with environments and improve their decisions during deployment. However, how anticipating future ou…
- arXiv cs.AIagentsBehavior Beyond Text: Evaluating Refusal Transfer Failure in LLM Agents
arXiv:2610.28982v1 Announce Type: new Abstract: While large language models are increasingly deployed as tool-calling agents, their safety evaluations still focus primarily on their ability to refuse harmful requests in…
- arXiv cs.AIagentsPerMIT: Securing Persistent Memory for LLM Agents via Machine-Checked Integrity Theorems and Scalable Community Trust
arXiv:2610.28987v1 Announce Type: new Abstract: Persistent memory is a largely undefended surface for injection and poisoning, and the same risk limits memory sharing among agents. We present PerMIT, a memory architectur…
- arXiv cs.AIagentsAgentPolicyForge: From Executable Environments to Policy Benchmarks and Adaptive Guards
arXiv:2610.28989v1 Announce Type: new Abstract: Customized agent deployments define policies over tools, resources, and execution conditions. Providing these policies in the task agent's prompt does not reliably prevent…
- arXiv cs.AIagentsAn Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning
arXiv:2610.29010v1 Announce Type: new Abstract: Radiation treatment planning requires balancing competing objectives to satisfy clinical criteria while accommodating physicians' preferences. This study aims to develop an…
- arXiv cs.AIagentsGenXR-Bench: Benchmarking Coding Agents for Interactive XR Development
arXiv:2610.29014v2 Announce Type: replace Abstract: Coding agents are rapidly advancing from single-file generation to long-horizon repository-scale engineering, yet the evaluation of their capabilities to author interac…
- arXiv cs.AIagentsInheritance as an Admission Test for LLM Prompt Merge Operators
arXiv:2610.29023v1 Announce Type: new Abstract: Large language model (LLM) agents are often improved by iterating until a fixed verifier is done. Once that verifier saturates, the loop has nothing left to climb. We inste…
- arXiv cs.AIresearchGRAIL: From Saliency to Semantics in Time-Series Explanation
arXiv:2610.29036v1 Announce Type: new Abstract: Explaining a time-series model requires both locating the evidence and extracting meaningful knowledge from it. Yet a single timestep is not a semantic unit: the meaningful…
- arXiv cs.AIresearchAutoFraming: Synthesizing Dynamic Frames of C Code with LLMs
arXiv:2610.29046v1 Announce Type: new Abstract: Large language models (LLMs) have shown considerable promise in synthesizing formal specifications from source code. However, existing approaches primarily focus on functio…
- arXiv cs.AIresearchDoes Every Instance Count Equally? Order Effects in LLM Multi-Instance Processing
arXiv:2610.29057v1 Announce Type: new Abstract: Users increasingly rely on large language models (LLMs) to analyse collections of independent inputs, such as product reviews or social media posts, and return a single agg…
- arXiv cs.AIresearchContext-Augmented, Session-Calibrated Blood Pressure Tracking from Photoplethysmography
arXiv:2610.29091v1 Announce Type: new Abstract: Objective.To distinguish the contributions of acquisition context and photoplethysmography (PPG) to session-calibrated blood pressure (BP) tracking.Approach. The original c…
- arXiv cs.AIresearchSame Answer, Different Reasons: Trace-Level Divergence in Multilingual Large Language Models
arXiv:2610.29092v1 Announce Type: new Abstract: Multilingual large language models are increasingly deployed in settings where visible reasoning traces support verification, education, and safety auditing, yet standard e…
- arXiv cs.AIresearchGRAM: Group-wise Rank-Aware Model Merging via Subspace Alignment
arXiv:2610.29110v1 Announce Type: new Abstract: Merging different models into a single model is highly desirable for multi-task deployment, particularly in regulated domains like healthcare. In such settings, models are…
- arXiv cs.AIagentsRecursive Self-Improvement on a Budget: Scoring Code Edits Before They Run
arXiv:2610.29121v1 Announce Type: new Abstract: A coding agent that rewrites its own scaffold has to choose which proposed edit to expand before that edit has been evaluated, and the search then has to return one agent.…
- arXiv cs.AIresearchStochIKM: Automated High-Fidelity Reconstruction of Individual Patient Data from Published Kaplan-Meier Curves
arXiv:2610.29122v2 Announce Type: replace Abstract: Individual patient data are the gold standard for secondary analysis of time-to-event evidence, but they are rarely released, and reconstruction from a published Kaplan…
- arXiv cs.AIresearchNormTune: Norm-Guided Parameter-Efficient Fine-Tuning for Reasoning-Intensive Tasks
arXiv:2610.29134v1 Announce Type: new Abstract: Full fine-tuning has achieved remarkable success on reasoning-intensive tasks, but it often requires substantial GPU resource consumption. Parameter-efficient fine-tuning (…
- arXiv cs.AIagentsLaVGuard: Selective Decoding for Contextual Value Drift
arXiv:2610.29135v1 Announce Type: new Abstract: A content-safe response can still promote priorities that conflict with its task: an assistant may demand compliance when asked to preserve autonomy. We study contextual va…
- arXiv cs.AIagentsSteering Black-Box Large Language Model Agents with Pitfall Anticipation World Model
arXiv:2610.29139v1 Announce Type: new Abstract: Frontier black-box Large Language Model (LLM) agents are proficient at long-horizon reasoning and precise action generation. However, when it comes to a specific agentic ta…
- arXiv cs.AIresearchTeachBack: Learning to Teach via Bidirectional Preference Optimization for On-Policy Self-Distillation
arXiv:2610.29167v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) enables a language model to learn from a Teacher instantiated from the same model but given access to privileged information, such as a r…
- arXiv cs.AIresearchWhen Multiple Choices Are Correct: Asymmetric Probability Allocation in Jev and Other Decision Models
arXiv:2610.29217v1 Announce Type: new Abstract: Decision models return normalized probability distributions over candidate choices, which downstream applications can use to select among choices. Although their providers…
- arXiv cs.AIresearchFrom Scores to Safe Sets: Exact Safety--Constrained Decoding for Medication Recommendation
arXiv:2610.29228v1 Announce Type: new Abstract: Recent generative medication recommendation systems ultimately produce sets of drugs, but drug--drug interaction (DDI) constraints depend on the set as a whole. A natural p…
- arXiv cs.AIagentsCrashGym: Measuring the Decision Value of Experimentation for LLM Agents in Counterfactual Market Crashes
arXiv:2610.29245v1 Announce Type: new Abstract: Language-model agents are increasingly asked to run experiments, yet benchmarks rarely measure whether those experiments improve the decisions they are meant to inform. We…
- arXiv cs.AIresearchARCANA: A Benchmark for Abstraction and Analogical Reasoning
arXiv:2610.29271v3 Announce Type: replace Abstract: Analogical reasoning is widely considered a fundamental component of human intelligence. Few benchmarks are designed to explicitly test far analogical reasoning - reaso…
- arXiv cs.AIresearchSame Probabilities, Different Advice: Gain-Loss Framing Effects in High-Stakes LLM Decision Support
arXiv:2610.29294v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support consequential decisions, yet their reliability under equivalent representations of uncertainty remains unclear…
- arXiv cs.AIresearchLLM-Based Exogenous World Modeling for Dynamic Scheduling
arXiv:2610.29308v1 Announce Type: new Abstract: Dynamic scheduling requires dispatching online arrivals while anticipating future jobs, as poor decisions can compound downstream costs under nonlinear tardiness objectives…
- arXiv cs.AIresearchSpatialBrain: Spatial Intelligence Growing from Experience
arXiv:2610.29317v1 Announce Type: new Abstract: Spatial reasoning requires more than access to geometric tools: a reasoner must decide when direct observation is sufficient and when to reconstruct, measure, or change ref…
- arXiv cs.AIagentsAgentMonopoly: Behavioral Patterns and Persona Control in LLM Agents
arXiv:2610.29330v2 Announce Type: replace Abstract: How do LLM agents' strategies differ, and how much can instructions to adopt a persona change their behavior over a game? We study these questions with AgentMonopoly, a…
- arXiv cs.AIagentsFrom Prompts to Posteriors: Can LLM Agents Perform Bayesian Inference in Context?
arXiv:2610.29331v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied across the scientific discovery pipeline, from synthesizing literature to generating hypotheses to informing experimen…
- arXiv cs.AIresearchSolving Go under Positional Superko: Sound Proof Transfer and New Board Values
arXiv:2610.29414v1 Announce Type: new Abstract: Positional superko (PSK) forbids recreating any earlier whole-board position. It is part of the Chinese rules as written and of the rules used in computer Go. Yet almost al…
- arXiv cs.AIresearchMERP: A Latent-Bottleneck Framework for Robust Multi-Modal Multi-Label Emotion Recognition
arXiv:2610.29430v1 Announce Type: new Abstract: Multimodal multi-label emotion recognition is important for affect-aware systems, but models trained with complete text, visual, and acoustic streams often degrade sharply…
- arXiv cs.AIresearchEvents, Not Pixels: Where World Models Get the Return Wrong
arXiv:2610.29435v1 Announce Type: new Abstract: World models are increasingly used for planning, where a planner ranks candidate actions by returns imagined by the model. However, these models are judged mainly by how we…
- arXiv cs.AIagentsPreCoMem: Predictive Cognitive Memory for Self-Evolving Long-Term Dialogue Agents
arXiv:2610.29467v1 Announce Type: new Abstract: Long-horizon dialogue agents need to keep user memories stable enough for personalization while adapting when the user genuinely changes. Existing memory systems often appe…
- arXiv cs.AIresearchRubricOpt: Self-Revision of Semantic Rubrics for Preference Optimization
arXiv:2610.29491v1 Announce Type: new Abstract: A model's failures can reveal gaps in the behavioral criteria guiding its training. We introduce RubricOpt, a framework that lets a policy revise these criteria within pref…
- arXiv cs.AIresearchAn Exact 93-Move Solution to a Nonlocal Crystal-Exchange Puzzle
arXiv:2610.29493v1 Announce Type: new Abstract: We determine the minimum number of directional commands needed to solve alevel of Order of the Sinking Star, modeled as a crystal-exchangepuzzle on an 11*11 board. A comman…
- arXiv cs.AIresearchParallel Thinking for Large Language Model with Path Diversity
arXiv:2610.29501v1 Announce Type: new Abstract: Parallel thinking has emerged as a promising paradigm for enhancing the reasoning capabilities of Large Language Models (LLMs) by exploring multiple reasoning paths simulta…
- arXiv cs.AIresearchFrom Association to Decision Value: Testing Paired Instruction Dependence for VLA Corpus Selection
arXiv:2610.29646v1 Announce Type: new Abstract: Choosing among robot demonstration corpora is a ranking problem: an upstream diagnostic must preserve which candidates produce better downstream policies, not merely correl…
- arXiv cs.AIresearchTraceForge: Distilling with Your Own Thinking
arXiv:2610.29680v3 Announce Type: replace Abstract: Using an LLM to generate training data for another is among the most general ways to train one, and it remains common practice. Some frontier teams have closed that rou…
- arXiv cs.AIagentsReal PMIDs, Wrong Papers: Harness Design for Biomedical Claim-Verification Agents
arXiv:2610.29812v1 Announce Type: new Abstract: Literature-searching language agents are becoming a standard component of scientific assistants for the life sciences, yet there is little controlled evidence on which part…
- arXiv cs.AIresearchCOMET: A coordinated multi-layer runtime monitoring framework for human-supervised AI-enabled safety systems
arXiv:2610.29816v1 Announce Type: new Abstract: Incorporating AI systems into safety systems requires monitoring to avoid silent faults and ensure safe and reliable operation. Single monitors often do not provide actiona…
- arXiv cs.AIagentsUserSWE: Evaluating Coding Agents in Multi-Turn Conversations with Dynamic Users
arXiv:2610.29822v1 Announce Type: new Abstract: As coding agents become more capable, developers increasingly use them to fix bugs through multi-turn interactions. Existing benchmarks do not adequately cover this scenari…
- arXiv cs.AIagentsToM2Vec: Continuous Theory-of-Mind Tokens for Multi-Agent Coordination
arXiv:2610.29934v1 Announce Type: new Abstract: Forming an accurate theory-of-mind (ToM) is key to successful multi-agent collaboration and requires reasoning under uncertainty to capture multiple possible partner states…