AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchZero-Shot Forecasting of In-Situ Soil Moisture and Temperature with a Time-Series Foundation Model
arXiv:2610.30971v1 Announce Type: new Abstract: Soil moisture and temperature govern plant-water availability and microbial activity, making them key indicators for evaluating land-restoration efforts on degraded landsca…
- arXiv cs.AIagentsColaBench: Evaluating Memory-Guided Knowledge Acquisition in Personal Agents
arXiv:2610.30989v1 Announce Type: new Abstract: Personal agents need to draw on long-term interaction history to retrieve and apply external knowledge suited to a user's current request. Even an answer grounded in releva…
- arXiv cs.AIresearchAgri-SCHOLAR: Simulation-Grounded In-Season Rolling Advisories for Agricultural Crops Using LLM-Bounded Optimization
arXiv:2610.31003v1 Announce Type: new Abstract: Existing agricultural advisories to farmers suffer from several limitations: (a) remain largely expert-driven, (b) do not adequately account for in-season weather, and (c)…
- arXiv cs.AIresearchMitigating Saliency Collapse: Robust Saliency-Aware Long-Text Image-Text Alignment
arXiv:2610.31005v2 Announce Type: replace Abstract: Long-text image-text alignment is essential for fine-grained scene understanding, yet existing methods mainly focus on extending context length or improving local align…
- arXiv cs.AIresearchEvaluating Artificial Wisdom (AW): A Trajectory-Based Framework for Context-Sensitive Decision Regulation
arXiv:2610.31012v1 Announce Type: new Abstract: Capability benchmarks measure what large language models can do, but not whether their recommendations remain appropriate as decision conditions change. This paper proposes…
- arXiv cs.AIagentsCANNBot-CAKE: Collaborative Agentic Kernel Evolution for Ascend NPU
arXiv:2610.31034v1 Announce Type: new Abstract: Efficient custom operators are essential for modern deep learning workloads, yet developing high-performance kernels for Ascend NPUs remains slow, expert-intensive, and dif…
- arXiv cs.AIresearchMultichoice Modeling: Exploring Decision Configuration Space under Uncertainty
arXiv:2610.31038v1 Announce Type: new Abstract: Decision support has become sophisticated at exploring uncertainty, but much less so at representing the architecture of the decision itself. As a result, the decision spac…
- arXiv cs.AIresearchAlgorithmic drift in generative adaptive learning
arXiv:2610.31041v1 Announce Type: new Abstract: Generative artificial intelligence promises to democratize personalized tutoring, yet the longitudinal stability of adaptive systems remains under-theorized. Current ethica…
- arXiv cs.AIresearchConflict-Aware Logit Adapters for Utility-Preserving Anti-Distillation
arXiv:2610.31046v1 Announce Type: new Abstract: While reasoning traces improve model capability, they also provide supervision signals for downstream distillation. Initial efforts to mitigate this issue rely on decoding-…
- arXiv cs.AIresearchDirecting to Diversify: Multi-Directional Search for Automatic Heuristic Design
arXiv:2610.31048v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong potential to automate heuristic design for NP-hard combinatorial optimization (CO) tasks without human intervention. R…
- arXiv cs.AIresearchDiagnosing the Explicit-to-Applied Theory of Mind Gap in LLMs
arXiv:2610.31060v1 Announce Type: new Abstract: As large language models are deployed in high-stakes roles such as therapy, education, and personal assistance, their social cognition must be assessed reliably. Current Th…
- arXiv cs.AIagentsSCOPE: Compiling Natural-Language Policies into Neurosymbolic Predicate Programs
arXiv:2610.31062v1 Announce Type: new Abstract: Policy enforcement for LLM agents has shifted from single-turn content moderation to compound, application-specific policies evaluated over multi-turn transcripts and tool-…
- arXiv cs.AIagentsDual Exam: Controlled Evaluation of Multimodal Agents and World Models
arXiv:2610.31066v2 Announce Type: replace Abstract: World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interac…
- arXiv cs.AIresearchCo-Recursive Semantic Self-Extension: A Mathematical Foundation for Open-Ended Intelligence
arXiv:2610.31097v2 Announce Type: replace Abstract: Artificial intelligence has advanced through scale, data, and computation, yet remains bounded by its representational framework. We ask what makes intelligence open-en…
- arXiv cs.AIresearchSolving Flood-It Puzzles: A Comparison of Tailored A* Search with Declarative Solver Approaches
arXiv:2610.31100v1 Announce Type: new Abstract: We present an optimized approach for finding minimal move sequences to solve Flood-It puzzles using A* search and compare it with approaches using SAT, Integer Programming,…
- arXiv cs.AIresearchDeepOpen: Decision-Oriented Intent Classification on BANKING77 and CLINC150
arXiv:2610.31104v2 Announce Type: replace Abstract: We present DeepOpen, a decision-Oriented intent-classification framework with dataset- specific systems for BANKING77 and CLINC150. On BANKING77, a single English class…
- arXiv cs.AIagentsWho Is the Influencer? Consensus Dynamics in Multi-Agent Systems
arXiv:2610.31105v1 Announce Type: new Abstract: Multi-agent LLM systems are increasingly used in practice, but their behavior is complex and hard to understand. We design a simple task to ask which model has the most inf…
- arXiv cs.AIagentsCan AI Co-Design Structures? An AI Agent for Early-Stage Structural Design
arXiv:2610.31113v1 Announce Type: new Abstract: Recent advances in large language models and agentic workflows offer a new paradigm to early-stage structural design translating design intent into structural models. Altho…
- arXiv cs.AIresearchConstraint Reasoning and Large Language Models Join Forces: Providing Contrastive Explanations for Real-World Optimisation-Based Applications
arXiv:2610.31119v1 Announce Type: new Abstract: We focus on optimisation-based Decision Support Systems in real-world applications. In this context, we aim to provide contrastive explanations that answer users' questions…
- arXiv cs.AIresearchSetCommit: Coordinated Token Commitments for Few-Step Diffusion Language Model Decoding
arXiv:2610.31120v1 Announce Type: new Abstract: Diffusion language models generate multiple token positions in parallel, but few-step decoding makes parallel commitment difficult: tokens that appear reliable individually…
- arXiv cs.AIagentsPost-Audit Mirage: Identifiability Limits of Offline Agent Verification
arXiv:2610.31130v1 Announce Type: new Abstract: Offline tests can fail to reveal whether an agent update will remain safe after deployment. We operationalize this post-audit mirage using matched safe and harmful lifecycl…
- arXiv cs.AIresearchRethinking Fisher Vectors for Second-order Multi-scale Deep Feature Aggregation in Scalable Scene Retrieval
arXiv:2610.31146v1 Announce Type: new Abstract: Aggregating CNN responses into a compact discriminative vector, given their lack of geometric invariance, is a challenge. To address this challenge, we propose a codebook-f…
- arXiv cs.AIresearchDifferent Tasks, Different Timesteps: Temporal Task-Aware Quantization for Diffusion Language Models
arXiv:2610.31198v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) introduce unique quantization challenges due to their iterative denoising process. In this work, we reveal that quantization sensitivity is…
- arXiv cs.AIresearchTrion-1: Unifying Language, Protein Sequence, and Structure with Diffusion Language Models
arXiv:2610.31215v1 Announce Type: new Abstract: We envision a general-purpose protein foundation model as a unified, interactive model of sequence, structure, and function, capable of understanding, generation, and cross…
- arXiv cs.AIresearchReward-Weighted Preference Optimization for Selective Combinatorial Optimization Problems
arXiv:2610.31239v1 Announce Type: new Abstract: Reinforcement learning has emerged as an effective approach for combinatorial optimization, but most existing methods focus on problems such as the Travelling Salesperson P…
- arXiv cs.AIresearchReducing Multi-Horizon Photovoltaic Forecast Error through Tree-Anchored Expert Combination
arXiv:2610.31248v1 Announce Type: new Abstract: A strong direct tree model may remain the best standalone photovoltaic forecaster, yet a weighted combination can reduce its residual errors. We examine whether complementa…
- arXiv cs.AIagentsPointerBench: A Diagnostic Benchmark for Fine-Grained GUI Grounding
arXiv:2610.31274v1 Announce Type: new Abstract: Multimodal Large Language Models have shown promising performance in computer-use tasks, from planning user workflows to grounding natural-language actions to precise UI ta…
- arXiv cs.AIagentsRIPPLE: Recovery Internalization through Process-Level Policy Learning and Effect-Aware Credit for Long-Horizon Agentic Coding
arXiv:2610.31276v1 Announce Type: new Abstract: Long-horizon coding agents can observe a failure and generate a plausible critique yet continue along the same incorrect trajectory. We call this the Critique-to-Action Han…
- arXiv cs.AIagentsThe Value of Memory in Language Agents
arXiv:2610.31303v2 Announce Type: replace Abstract: Memory enables language agents to carry useful distinctions from past experience into future decisions. Its value depends on which distinctions survive, whether a bound…
- arXiv cs.AIagentsSubgoal-aware Memory Graph for GUI Agent
arXiv:2610.31307v1 Announce Type: new Abstract: GUI agents aim to automate complex user tasks by interacting with mobile interfaces, but ef- fective decision-making in long-horizon set- tings requires reusing prior exper…
- arXiv cs.AIresearchValuSpec: Plug-and-Play Candidate Valuation before Target Verification for Tree-Based Speculative Decoding
arXiv:2610.31338v1 Announce Type: new Abstract: Tree-based speculative decoding accelerates large language model inference by verifying multiple candidate branches in parallel. However, in practical serving scenarios, si…
- arXiv cs.AIagentsMuffin - A Shared Memory Buffer for Asynchronous AI Agents
arXiv:2610.31355v1 Announce Type: new Abstract: The rise of Agentic AI systems has changed the landscape of artificial intelligence by enabling strong reasoning capabilities through specialized multi-agent interaction wi…
- arXiv cs.AIagentsRIDAR: Safeguarding Research Integrity in Autonomous Research Agents via Automated Detection and Runtime Intervention
arXiv:2610.31372v2 Announce Type: replace Abstract: Autonomous research agents are increasingly used to automate large portions of scientific research, yet they are prone to research integrity violations (RIVs): behavior…
- arXiv cs.AIagentsCertified Execution Harness for Agentic AI: Safe and Least-Intrusive Petri-Net Supervisory Control Between Reasoning and Action
arXiv:2610.31376v1 Announce Type: new Abstract: This paper studies the problem of safe tool execution for large language model (LLM) agents under prompt injection. Using Petri nets, we formalize the execution harness bet…
- arXiv cs.AIresearchPhysTrace: Interpretable Temporal Evaluation of Physical Consistency in Video Generative Models
arXiv:2610.31429v1 Announce Type: new Abstract: World action models increasingly rely on pretrained video models assumed to capture physical dynamics for prediction, planning, and action generation. Existing evaluations…
- arXiv cs.AIagentsConservative Meta-Agent Search: Architecture Adaptation under Non-Stationarity
arXiv:2610.31436v1 Announce Type: new Abstract: Automated agentic-system design is typically evaluated on static task suites with immediate scalar rewards. Deployed systems face persistent shift, delayed dependent feedba…
- arXiv cs.AIresearchDIAL: Steerable Language Models with Distilled Instruction-Adherence Levels
arXiv:2610.31438v1 Announce Type: new Abstract: When a user says "Keep it short", how short should the LLM's response be? More generally, users and applications require different levels of instruction adherence, but prom…
- arXiv cs.AIagentsAdaptive Skill Granularity for Coding Agents: Runtime Routing and Macro-to-Micro Recovery
arXiv:2610.31461v1 Announce Type: new Abstract: Reusable skills allow large language model agents to package task-specific procedures, tool affordances, and execution guidance into modular units. Prior work has largely s…
- arXiv cs.AIresearchFairFRESH: A Neuro-Symbolic Framework for Fair and Explainable Household Food Recommendation
arXiv:2610.31506v1 Announce Type: new Abstract: Recommender systems typically serve one user at a time. However, in households, members share a finite pantry and follow different dietary rules, making independent recomme…
- arXiv cs.AIagentsDuoCook: An Overcooked-Inspired Benchmark for Visual Planning and Coordination
arXiv:2610.31511v1 Announce Type: new Abstract: Coordinating two players in a cooking task requires a vision-language agent to track changing scene states, sequence recipe steps, and allocate shared resources under a tim…
- arXiv cs.AIresearchFrom Prompt Rules to Golden Data Model: Production-Scale Generation of Personalized, Compliant Pharmaceutical Claims
arXiv:2610.31519v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate domain-specific commercial & medical content (e.g., claims, statements, and promotional phrases) in regulated…
- arXiv cs.AIresearchJev-DLC: Decision-Level Continual Learning from Typed Feedback
arXiv:2610.31521v1 Announce Type: new Abstract: Individual preferences often become visible only after deployment, when a user accepts one decision or revokes it in favor of another. Jev-style typed interfaces make this…
- arXiv cs.AIresearchBeyond Causal Masks: Auditing and Localizing Hidden Future-Token Leakage in Adaptive Sequence Models
arXiv:2610.31522v1 Announce Type: new Abstract: Hidden future-token leakage can create false architectural gains: an autoregressive model may appear substantially better under teacher-forced evaluation while its free-run…
- arXiv cs.AIagentsContestable Agents for Data Governance: Recording Human Stewardship of AI-Generated Metadata Across Structured and Unstructured Systems
arXiv:2610.31553v1 Announce Type: new Abstract: Industrial organizations hold operational knowledge in structured records, such as telemetry, point lists, and transactions, and in unstructured sources, such as manuals, s…
- arXiv cs.AIresearchWhat Makes a Good Unmasking Policy? A Controlled Study of Learned Unmasking in Diffusion Language Models
arXiv:2610.31576v1 Announce Type: new Abstract: Masked diffusion language models generate tokens in parallel, but their efficiency depends on which predictions are committed. Learned unmasking policies improve the speed-…
- arXiv cs.AIresearchWho Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust Calibration
arXiv:2610.31579v1 Announce Type: new Abstract: Research on sycophancy asks whether large language models (LLMs) bend towards what their users want to hear. We ask the reverse question: when an LLM is confident, consiste…
- arXiv cs.AIresearchSimulated Control Evals
arXiv:2610.31593v1 Announce Type: new Abstract: Control evaluations measure whether safeguards can prevent an AI model from causing undesired outcomes even when it is intentionally trying to do so. These evaluations typi…
- arXiv cs.AIagentsEpiSEM-Bench: Evaluating Safety and Evidence Recovery in LLM Agents under Missing Evidence
arXiv:2610.31650v1 Announce Type: new Abstract: Tool-using language model agents rely on environmental facts to decide whether an action is permitted. When a tool response omits a safety-relevant fact, an agent may carry…
- arXiv cs.AIresearchDirect Pass@$k$ Optimization for Thought Pruning: Balancing Quality and Diversity in Test-Time Reasoning
arXiv:2610.31667v1 Announce Type: new Abstract: Test-time scaling has emerged as a key inference strategy for reasoning models, where a model generates a large number of candidate solutions in the hope of finding at leas…
- arXiv cs.AIagentsLighthouse: On Building a Trustworthy Digital Assistant for Exploring History with Civil Rights Archives
arXiv:2610.30158v1 Announce Type: cross Abstract: Artificial intelligence (AI), as a decision-support aid, provides new tools for studying history effectively using multimodal data, including text, images, and audio. We…