AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchImage Synthesis as an Intermediate for Controllable Time Series Generation
arXiv:2610.05211v1 Announce Type: new Abstract: Semantic-driven time-series generation offers a promising way to improve downstream learning in few-shot forecasting, but directly generating numerical sequences from langu…
- arXiv cs.AIagentsSafe Context Switching for Agents in the Wild: Mitigating Subspace Interference via Orthogonal Adaptation
arXiv:2610.05219v1 Announce Type: new Abstract: Most Large Language Models exhibit a fundamental tension between two sequential tasks, such as logical reasoning and safety alignment. The high-variance internal states req…
- arXiv cs.AIagentsLook Before You Leap: Thermodynamic Arbitration of Parametric and Non-Parametric Knowledge in LLM Agents via Self-Regulating Memory Architectures
arXiv:2610.05223v1 Announce Type: new Abstract: The architecture of modern LLMs consists of a profound cognitive polarization. LLMs possess implicit intuition encoded in their parameters, yet rely on a disconnected, expl…
- arXiv cs.AIresearchGFGE: Unifying Explainable AI Methods through an Interpretation Framework
arXiv:2610.05225v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) encompasses methods that draw on different sources of information and address different explanatory needs. A common framework is n…
- arXiv cs.AIresearchLearning from imperfect teachers for low-resource acoustic generalization
arXiv:2610.05256v1 Announce Type: new Abstract: Knowledge distillation (KD) improves low-resource acoustic learning by enriching one-hot supervision with the softened predictive distribution of a fixed teacher network. H…
- arXiv cs.AIagentsWhen Agent Context Goes Stale: Incoherence in Volatile Agent Context
arXiv:2610.05281v2 Announce Type: replace Abstract: Modern agents increasingly ground their reasoning in observations returned by tools, such as file contents read from a workspace. However, the data sources underlying t…
- arXiv cs.AIagentsFusion is the New Mutation: Bandit-Guided Evolution on Workflow Graphs
arXiv:2610.05284v1 Announce Type: new Abstract: Automated agentic workflow optimization relies on costly evaluations, making it essential to allocate a limited evaluation budget effectively. Multi-parent fusion can reuse…
- arXiv cs.AIagentsReadable Before Actionable: Causal Tracing of Indirect Prompt Injection
arXiv:2610.05295v1 Announce Type: new Abstract: Indirect prompt injection causes LLM agents to follow commands embedded in external data. A probe may distinguish instructions from data without identifying a state edit th…
- arXiv cs.AIagentsMESH-Harness: Self-Improving Agent Harnesses via Bandit-Guided Compositional Evolution
arXiv:2610.05300v1 Announce Type: new Abstract: An agent harness is the code that organizes context, maintains state, and coordinates tool calls for a language model. We study how to improve the harness under a limited e…
- arXiv cs.AIagentsAgentDiscover: Autonomous Discovery with Minimal Search Scaffolding
arXiv:2610.05334v1 Announce Type: new Abstract: Frameworks that use large language models for scientific discovery typically rely on a fixed, human-designed algorithm that decides what the model sees at each step, leavin…
- arXiv cs.AIresearchEnGRICH: Enhancing Generative Reward Modeling with Critiques from Humans
arXiv:2610.05370v2 Announce Type: replace Abstract: Generative reward models (GRMs) are important for LLM optimization. Unlike scalar reward models, GRMs generate natural-language critiques alongside preference judgments…
- arXiv cs.AIresearchLearning Field Reconstruction from Incomplete Data by Globally Correcting Local Estimates
arXiv:2610.05375v2 Announce Type: replace Abstract: Reconstructing physical fields from training samples that are always incomplete requires learning spatial structure from fragmented observations. Existing context--quer…
- arXiv cs.AIagentsSibyl: An Efficient Small-large Model Collaboration Framework for Long-horizon Tasks
arXiv:2610.05383v1 Announce Type: new Abstract: Small language models (SLMs) offer a promising foundation for on-device agents through low-latency, resource-efficient inference, yet limited reasoning and planning capabil…
- arXiv cs.AIagentsMMPostTrainBench: Benchmarking Autonomous Research for Multimodal Post-Training
arXiv:2610.05398v1 Announce Type: new Abstract: Autonomous research seeks sustained model improvements through iterative experimentation and feedback. LLM agents show promise in automating machine learning and language-m…
- arXiv cs.AIagentsCASE: Cost-Aware Stopping for Efficient Long-Video Agents
arXiv:2610.05400v1 Announce Type: new Abstract: Long-video agents can actively gather question-relevant evidence, but they typically leave a central decision implicit: when has the agent seen enough to answer? We propose…
- arXiv cs.AIagentsPharmAgent: Constraint-Aware Search with Frozen Language Models for Molecular Optimization
arXiv:2610.05431v1 Announce Type: new Abstract: Molecular optimization must improve target activity and satisfy developability constraints within limited evaluation budgets. Classical methods require tailored rules or tr…
- arXiv cs.AIagentsTeleTune: Evolving Agent Skills From Offline Telemetry
arXiv:2610.05437v2 Announce Type: replace Abstract: Computer-use agents need to capture procedural knowledge of how people use software. User telemetry offers a scalable source of this knowledge. However, learning reusab…
- arXiv cs.AIresearchAI Safety via Debate is Compromised by Cognitive Biases
arXiv:2610.05461v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) has played a central role in making large language models responsive to human instructions. However, human evaluators ofte…
- arXiv cs.AIresearchHallucination Across the Reasoning Lifecycle: Interface Visibility, Causal Evidence, and Release Control in Large Reasoning Models
arXiv:2610.05472v1 Announce Type: new Abstract: Reasoning errors can propagate into later decisions and memory. This survey synthesizes 312 papers and first-party reports on text-based reasoning hallucinations around thr…
- arXiv cs.AIagentsHierarchical Reinforcement Learning with Stable Temporal Abstraction for Language Model Agents
arXiv:2610.05473v1 Announce Type: new Abstract: Hierarchical reinforcement learning improves long-horizon control by organizing primitive actions around persistent subgoals and assigning credit at multiple temporal scale…
- arXiv cs.AIagentsCodeForge-MA: Execution-Verified Multi-Agent Learning with Language-Conditioned LoRA for Multilingual Code Generation
arXiv:2610.05481v1 Announce Type: new Abstract: Large language models for code generation often fail on execution, multilingual coverage, and contamination control, especially under frozen backbone constraints. We presen…
- arXiv cs.AIresearchSkillGATE: Gate-Aware Monte Carlo Tree Search for Skill Retrieval
arXiv:2610.05489v1 Announce Type: new Abstract: Skill Retrieval (SR) aims to identify the most relevant skills from external skill libraries, and becomes increasingly challenging as libraries grow in scale and diversity.…
- arXiv cs.AIresearchThe Functional Structure of Post-Compression Recovery in Low-Rank LLMs
arXiv:2610.05504v1 Announce Type: new Abstract: Different low-rank compression methods can produce compressed LLMs that respond differently to the same post-compression recovery procedure, and relative advantages observe…
- arXiv cs.AIresearchWhat Does Fr\'echet Distance Measure? A Directional Decomposition
arXiv:2610.05518v1 Announce Type: new Abstract: The Fr\'echet distance is a de facto standard for evaluating generative models across domains, appearing as FID for images and FVD for videos. It summarizes the discrepancy…
- arXiv cs.AIagentsHave I Scene This Before? Spatially Grounded Conversational Memory for Complex Queries in Egocentric Assistants
arXiv:2610.05526v1 Announce Type: new Abstract: Egocentric assistants must connect what users say with what they see across long interaction histories. We formalize this challenge as Spatially grounded Conversational Rea…
- arXiv cs.AIagentsDelegationBench: Measuring When AI Agents Should Ask Before Acting
arXiv:2610.05532v1 Announce Type: new Abstract: AI agents that send emails, edit files, and make purchases must decide when to act on their own and when to check with the user first. This decision is usually evaluated by…
- arXiv cs.AIresearchMore Claims, Less Evidence: Bounded Verification of AI-Generated Digital Knowledge Artifacts
arXiv:2610.05547v1 Announce Type: new Abstract: Digital libraries, repositories, and AI-mediated knowledge services increasingly rely on generative systems to produce summaries, descriptions, and other multi-claim knowle…
- arXiv cs.AIagentsLifeLong Digital Twin: A Unified Modeling Paradigm and Agent Harness for Event-Driven Lifelong Health State Trajectories
arXiv:2610.05566v1 Announce Type: new Abstract: Human health is a continuous, dynamic trajectory shaped by the cumulative interplay of biological processes, clinical events, behaviors and environmental exposures across t…
- arXiv cs.AIagentsFactoriax: A GPU-Accelerated Factorio-Style Simulator for Reinforcement Learning
arXiv:2610.05569v1 Announce Type: new Abstract: We introduce Factoriax, a GPU-accelerated factory-building simulator written in JAX. In Factoriax, an agent must collect resources, build machines using those resources, an…
- arXiv cs.AIresearchBetter Retrieval, Limited Clustering Gains: A Controlled Study of Multilingual Company Entity Resolution
arXiv:2610.05573v2 Announce Type: replace Abstract: Company name retrieval and final entity clustering can respond differently to encoder adaptation. We study this dependency through a controlled pipeline: train multilin…
- arXiv cs.AIagentsDREAM: Dynamic Resolution Assignment For Multimodal Multi-agent Debate
arXiv:2610.05615v3 Announce Type: replace Abstract: Multi-agent debate (MAD) has emerged as an effective paradigm to improve the reasoning capabilities of large language models (LLMs) and is increasingly being extended t…
- arXiv cs.AIagentsA Framework for Automated Multi-Source Satellite Data Analytics and LLM-Based Report Generation
arXiv:2610.05625v2 Announce Type: replace Abstract: This paper presents the workflow for building an automated ArcGIS Pro tool using ArcPy to extract the Land Surface Temperature (LST) from Landsat 7, 8 and 9 datasets. T…
- arXiv cs.AIresearchThe GenAI4IDN Benchmark 3.0 - a Public Tool to Assess Generative AI Tools for the Design of Interactive Digital Narratives
arXiv:2610.05633v1 Announce Type: new Abstract: This paper presents GENAI4IDN Benchmark 3.0, the third iteration of an evaluation framework to assess Generative AI tools for creating Interactive Digital Narratives (IDNs)…
- arXiv cs.AIagentsVisual Grounding Safety in Vision-Language Models
arXiv:2610.05637v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly trained to generate structured outputs like points and bounding boxes that downstream interfaces, agents, and robots can act…
- arXiv cs.AIresearchHow Should a Prompt Optimizer Spend a Tight Budget? BudgetAPO with Noise-Adaptive Evaluation
arXiv:2610.05671v3 Announce Type: replace Abstract: Automatic prompt optimization (APO) has been widely employed to adapt large language models without updating their weights, yielding promising results. However, existin…
- arXiv cs.AIresearchDo Time-Series QA Systems Read the Time Series? Evidence Use and Reasoning Reliability
arXiv:2610.05686v1 Announce Type: new Abstract: In recent years, time-series question answering (QA) systems have made significant progress. However, generating a correct answer does not show whether retaining the suppli…
- arXiv cs.AIresearchToward AI Trustworthiness: Finding Analytically Proven Forward-Invariant Sets for AI-Controlled Systems
arXiv:2610.05689v1 Announce Type: new Abstract: Neural-network (NN) controllers are increasingly used in nonlinear control systems, but their highly nonlinear behavior makes them difficult to explain and verify, raising…
- arXiv cs.AIresearchFrom Token-Max to Outcome-Max: How You Use AI Determines Its Productivity
arXiv:2610.05697v1 Announce Type: new Abstract: Generative artificial intelligence (AI) models can perform increasingly complex tasks, yet greater AI usage does not necessarily translate into proportional productivity ga…
- arXiv cs.AIagentsSecond-Order Problem Solving for Recursive Self-Improvement in Formal Verification
arXiv:2610.05701v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) enables agents to iteratively optimize their workflows via execution feedback. However, standard RSI typically operates as a first-orde…
- arXiv cs.AIresearchFreSia: Frequency-Semantic Instantiation and Alignment for Multivariate Time Series Analysis
arXiv:2610.05726v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential in multivariate time series forecasting and anomaly detection. Existing studies predominantly inject temporal infor…
- arXiv cs.AIagentsMining Agent Skills from Production Traces
arXiv:2610.05777v1 Announce Type: new Abstract: Agent skills that record procedural instructions are increasingly mined from execution traces rather than curated by hand. Skill-mining pipelines often use known task outco…
- arXiv cs.AIagentsAgentic-ZTA: A Multi-Agent Architecture for Autonomous Zero Trust Enforcement
arXiv:2610.05782v1 Announce Type: new Abstract: Agentic AI is emerging as a promising paradigm for automating complex cybersecurity decisions, yet its use in enforcing zero trust introduces significant challenges in safe…
- arXiv cs.AIagentsTopology-Conditioned Backdoors: Language Models That Insert Vulnerabilities When They Infer They Are in a Multi-Agent System
arXiv:2610.05793v1 Announce Type: new Abstract: A language model may behave safely in a single-agent evaluation yet produce vulnerable code when its context suggests that it is part of a multi-agent system. We study this…
- arXiv cs.AIresearchA Testable Theory of Atomic Features
arXiv:2610.05794v1 Announce Type: new Abstract: We develop and test a theory of language model representations in which there exist atomic features. Our main theoretical insight is that in such a model, sparse dictionari…
- arXiv cs.AIresearchDiMOS: Doob-Guided Inference-Time Multi-Objective Search for Scientific Design
arXiv:2610.05808v2 Announce Type: replace Abstract: Scientific design often requires jointly satisfying multiple objectives and constraints. Pretrained masked diffusion models provide a generative foundation for this tas…
- arXiv cs.AIresearchNash Equilibrium Text: A Game-Theoretic Decoding Framework for Text Generation
arXiv:2610.05817v1 Announce Type: new Abstract: Text revision has become an integral component of large language models. This paper formulates revision such that it admits a Nash equilibrium: Token positions are players,…
- arXiv cs.AIresearchData-Driven Personas for Survey Simulation: Insights into Simulation Alignment Across Data-Access Regimes
arXiv:2610.05828v2 Announce Type: replace Abstract: Large language models (LLMs) offer new opportunities for public opinion research by enabling early prediction of survey responses, potentially reducing the cost and tim…
- arXiv cs.AIagentsMeasurement-First Auditing of Agentic Leaderboards: Contamination Susceptibility, Matched-Control Re-evaluation, and Scorer Validation
arXiv:2610.05830v1 Announce Type: new Abstract: Agentic leaderboards increasingly evaluate systems on public benchmarks whose task statements and solution-bearing artifacts can remain accessible. We propose a measurement…
- arXiv cs.AIagentsRequest Order Matters: Cache-History Sensitivity in Selective KV-Cache Reuse for Rolling Agents
arXiv:2610.05833v1 Announce Type: new Abstract: Long-running agents repeatedly call an LLM while retaining most of their document window, evicting old documents, and appending new ones. These rolling updates break exact…
- arXiv cs.AIagentsMiniCorp: The Last Mile to an AI Agent Corporation
arXiv:2610.05912v2 Announce Type: replace Abstract: The last mile toward enterprise AGI is a company that runs itself. Training and adapting such agents require longitudinal enterprise data, which remain scarce, costly t…