AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsPlant Memory: Technical Language Processing and a Verified Maintenance Ontology for Agent-Accessible Failure Knowledge from SAP PM Work Orders
arXiv:2610.19131v1 Announce Type: new Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis. Short texts are abbrev…
- arXiv cs.AIresearchGraph-Based Orchestration of Heterogeneous AI Models: A Control Node Approach to Composite Intelligence
arXiv:2610.19136v1 Announce Type: new Abstract: We present a graph-based framework for Composite AI systems that integrate multiple AI techniques to address complex problems. We describe an architecture using specialized…
- arXiv cs.AIresearchCompiling Expert Procedures into Verified Programs: When a Small Model Is Enough
arXiv:2610.19148v2 Announce Type: replace Abstract: In procedural tool-use domains, how much of the gap between base models is procedure rather than capability? We build an explicit program from a teacher's traces and ru…
- arXiv cs.AIagentsAgentCIScope: Grounded Contextual Integrity Evaluation for LLM Agents
arXiv:2610.19158v1 Announce Type: new Abstract: LLM agents are becoming increasingly capable of handling daily workspace tasks by interacting with application environments through tool calls. However, as agents read and…
- arXiv cs.AIagentsInto the Unknown: Benchmarking AI agents on open scientific research problems
arXiv:2610.19159v1 Announce Type: new Abstract: Can AI agents carry out research on open scientific problems? We introduce Into the Unknown, a benchmark that provides an agent with a science paper along with a research d…
- arXiv cs.AIresearchListQA: A Benchmark for Evaluating List-Formatted Factual Knowledge Retrieval in Large Language Models
arXiv:2610.19165v1 Announce Type: new Abstract: Many real-world questions demand not a single fact but an organized collection of them, yet existing factual knowledge benchmarks almost exclusively target single answer re…
- arXiv cs.AIagentsVerification Turns Capability Gaps into Routing Decisions: Small Language Models for Clinical Documentation
arXiv:2610.19169v1 Announce Type: new Abstract: Clinical note generation from doctor--patient dialogue is high-volume and hallucination-intolerant: a fabricated laboratory value can create patient-safety risk, not a qual…
- arXiv cs.AIresearchLearning from Self-Generated Responses: Reliability--Uncertainty Self-Distillation for Reasoning
arXiv:2610.19176v1 Announce Type: new Abstract: Reference solutions and question-specific rubrics are not always available to guide the teacher in self-distillation. A large language model's own solution attempts offer a…
- arXiv cs.AIresearchMulti-System Cognitive Steering for Generative Communication
arXiv:2610.19177v1 Announce Type: new Abstract: A fundamental bottleneck for translating thoughts to speech is the high physical cost of motor input forcing a strict tradeoff between communication speed and expressivity.…
- arXiv cs.AIagentsIdentity, Incentives, and Cooperative Behavior for AI: Reverse-Engineering Multiagent Cooperation
arXiv:2610.19188v1 Announce Type: new Abstract: The behavior of AI systems increasingly depends on the extent to which agents cooperate or coordinate with one another, in ways that may be desirable or not depending on th…
- arXiv cs.AIresearchEmbedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization
arXiv:2610.19198v1 Announce Type: new Abstract: With the growing number of LLMs available, selecting which one to use for a prompt has become a key question. A large part of the routing literature relies on semantically…
- arXiv cs.AIresearchPREFER: From Player Experience to Personalized Game Refinement
arXiv:2610.19213v1 Announce Type: new Abstract: Understanding how large language models (LLMs) evaluate gameplay experience is important for using their feedback to guide game design. However, overall ratings alone provi…
- arXiv cs.AIresearchREPORT-OPS: Hybrid Evidence-Guided Reporting with Human-Supervised Refinement for HPC
arXiv:2610.19222v1 Announce Type: new Abstract: Operational reporting for high-performance computing (HPC) facilities requires combining information from monitoring services, schedulers, incident and maintenance records,…
- arXiv cs.AIresearchDefinition Grounding in Theory-Level Auto-formalization
arXiv:2610.19223v1 Announce Type: new Abstract: LLM-based auto-formalization systems can now generate formally verified Lean code at unprecedented rates. However, a formalization advances mathematical research only when…
- arXiv cs.AIagentsAgentic Self-Awareness: Aligning Knowing, Acting, and Holding
arXiv:2610.19226v1 Announce Type: new Abstract: Frontier AI agents increasingly act in environments where seemingly solvable tasks may lack prerequisites, contain conflicting requirements, or reveal blockers only during…
- arXiv cs.AIresearchWrite Once, Plan Many: Building Reusable Visual Planning Systems from One Scene
arXiv:2610.19234v1 Announce Type: new Abstract: Vision-language models (VLMs) can reason about visual planning tasks, but querying them for every instance incurs repeated inference cost and latency. Generating reusable p…
- arXiv cs.AIagentsMemeTrace: A Multimodal LLM-Based Agent for Safety-Aware Meme Provenance Analysis
arXiv:2610.19267v1 Announce Type: new Abstract: Online memes are often carriers of unsafe content such as disinformation and propaganda. Their rapid evolution in response to news events and strong dependence on contextua…
- arXiv cs.AIagentsWhose turn is it? Context-guided model routing for stateful agents
arXiv:2610.19292v1 Announce Type: new Abstract: Model routing can reduce the cost of LLM applications by assigning simpler requests to cheaper models without sacrificing the quality of the response. However, most routers…
- arXiv cs.AIresearchBeyond ICD Codes: Semantic IDs for Generative Medical Coding
arXiv:2610.19301v1 Announce Type: new Abstract: Generative approaches to automatic International Classification of Diseases (ICD) coding use large language models (LLMs) to predict ICD codes from clinical documents. Howe…
- arXiv cs.AIresearchGeneralization Analysis of Biased Stochastic Gradient Methods for Minimax Problems
arXiv:2610.19322v1 Announce Type: new Abstract: Minimax optimization refers to a class of optimization problems with some variables to minimize and other variables to maximize. Biased stochastic gradient methods have sho…
- arXiv cs.AIresearchCan We Believe AI Peer Review?
arXiv:2610.19339v1 Announce Type: new Abstract: As large language models become widely used in scientific review and manuscript revision, AI scores are increasingly serving as feedback for assessing paper quality and gui…
- arXiv cs.AIagentsWhen Is Smaller Greener? Right-Sizing Language Models for Agentic AI
arXiv:2610.19345v2 Announce Type: replace Abstract: AI agents use a large language model (LLM) to plan and act over many steps. Which model should an agent use, so that its tasks are completed reliably with the least ene…
- arXiv cs.AIresearchSteering Vectors for Competing Ethical Frameworks Are Interchangeable: A Competing-Target Test for Activation Steering
arXiv:2610.19359v1 Announce Type: new Abstract: Activation steering adds a vector to a model's hidden states to control a named behaviour. A gain on that behaviour, however, does not show that the vector controls it dire…
- arXiv cs.AIresearchDANGERLENS: Probing Dangerous Representations Hidden by Safety Alignment
arXiv:2610.19365v1 Announce Type: new Abstract: Safety alignment teaches language models to refuse harmful requests, yet the internal accessibility of hazardous concepts can retain traces of earlier training. Can checkpo…
- arXiv cs.AIagentsSeeing, Maintaining, and Learning: The Evolution of Multimodal Agent Memory
arXiv:2610.19366v1 Announce Type: new Abstract: Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating information across multiple mo…
- arXiv cs.AIagentsDeLoop: Repeated Actions as Self-Supervision for Long-Horizon Agents
arXiv:2610.19376v1 Announce Type: new Abstract: Language-model agents that run long tasks often redo work they have already done: they re-issue a tool call they made earlier and get back exactly the same observation, a s…
- arXiv cs.AIagentsEvoWeave: Composing Reusable Agent Experience through Operation Level Graphs
arXiv:2610.19381v1 Announce Type: new Abstract: Different tasks often require interactive agents to perform similar operations at intermediate steps. Retrieving an entire past workflow can introduce irrelevant steps, whe…
- arXiv cs.AIagentsixi-sLM: On-Device sLM for AI Call Agent Service
arXiv:2610.19382v1 Announce Type: new Abstract: Running an AI call agent on-device makes it private, network-independent, and free of per-query cloud cost, but shipping one as a real-world service imposes constraints a c…
- arXiv cs.AIagentsSTRATA: Self-Maintaining Structured Experience Graphs for Self-Evolving Language Agents
arXiv:2610.19386v1 Announce Type: new Abstract: Large language model (LLM) agents can self-evolve at test time by accumulating experience: retrieving relevant memories before acting and writing new lessons back afterward…
- arXiv cs.AIagentsEpiGuard: An Autonomous Infectious-Disease Early Warning Agent Platform
arXiv:2610.19396v1 Announce Type: new Abstract: Infectious disease outbreaks often spread rapidly before signs of widespread transmission become apparent, leaving a big challenge for rapid response and effective interven…
- arXiv cs.AIagentsSERO: Learning from Executable Oracle Continuations for Long-Horizon Agentic Reinforcement Learning
arXiv:2610.19397v1 Announce Type: new Abstract: Long-horizon agentic RL is constrained by the futures visited by the current policy. When rollouts fail to reach useful behaviors, improved credit assignment cannot provide…
- arXiv cs.AIagentsAgentSafeEvo: Adversarial Co-Evolution for LLM Agent Safety
arXiv:2610.19422v1 Announce Type: new Abstract: Large language model (LLM) agents accomplish complex tasks through multi-turn interactions with external tools. However, malicious content embedded in user queries, tool de…
- arXiv cs.AIresearchBeyond the Trial-and-Error Loop: Hybrid Projection and Automated Tuning for Distributed Training
arXiv:2610.19423v1 Announce Type: new Abstract: Configuring distributed LLM training across hundreds of GPUs requires jointly optimizing tensor, pipeline, expert, context, and data parallelism alongside micro-batch size,…
- arXiv cs.AIagentsEvaluating Agentic Capabilities Before Post-Training: An End-to-End Approach
arXiv:2610.19425v1 Announce Type: new Abstract: Agentic capabilities are increasingly important for modern LLMs, yet remain difficult to evaluate during pretraining. Existing approaches typically rely on static trajector…
- arXiv cs.AIresearchRecognition Is Not Grounding: Benchmarking Multilingual Financial Evidence Extraction
arXiv:2610.19432v2 Announce Type: replace Abstract: Comparing financial disclosures across languages requires identifying shared accounting concepts and recovering all numerical facts that express them. Existing benchmar…
- arXiv cs.AIagentsEvoProbe: Evaluation-Driven Benchmark Evolution for LLM Agents
arXiv:2610.19433v1 Announce Type: new Abstract: Static benchmarks for large language model (LLM) agents face saturation and data contamination risks, motivating continual updates to evaluation tasks. However, aggregate s…
- arXiv cs.AIresearchIntegrating Simulation and Chain-of-thought Reasoning in Multimodal-Language Models For Physical Reasoning
arXiv:2610.19441v1 Announce Type: new Abstract: Multimodal language models often need to reason about the physical dynamics of the world in order to answer questions appropriately. Various methods have emerged for solvin…
- arXiv cs.AIresearchxLightGCN: Explainable Graph Neural Network Based Recommendation Systems with Most Influential Peers
arXiv:2610.19446v1 Announce Type: new Abstract: Recommendation systems, systems that predict a user's preference for items in order to curate that user's feed, are a ubiquitous and central feature in online social networ…
- arXiv cs.AIresearchAre You Reading the Right Thing? Rethinking Internal Signals for Prompt-Injection Detection
arXiv:2610.19452v1 Announce Type: new Abstract: Several recent studies propose detecting prompt injections from a language model's internal state. However, these methods do not measure a single security property. Residua…
- arXiv cs.AIagentsAdCoEvo: A Co-Evolving Multi-Agent Advertising Delivery System
arXiv:2610.19454v1 Announce Type: new Abstract: Digital advertising is an important means for platforms to reach potential users and drive business growth. Advertising delivery is the core link between marketing objectiv…
- arXiv cs.AIagentsPFedMA: Who Should Join Next as Federated Multi-Agent Orchestration Evolves?
arXiv:2610.19458v1 Announce Type: new Abstract: Federated Multi-Agent Systems (FedMAS) offer a promising paradigm for collaborative reasoning among LLM-based agents while keeping raw client data decentralized. However, r…
- arXiv cs.AIagentsMemCode: Discrete Semantic Representations for Long-Term Agent Memory
arXiv:2610.19472v1 Announce Type: new Abstract: Long-term memory remains a fundamental bottleneck for large language model (LLM) agents across sessions. Existing systems typically adopt a write-then-retrieve paradigm, st…
- arXiv cs.AIagentsWhen Agent Memory Needs to Compute: Evidence Access and Executable Aggregation
arXiv:2610.19474v2 Announce Type: replace Abstract: Questions about an agent's history often require aggregating events, which retrieval alone does not resolve. We combine source-preserving evidence access with executabl…
- arXiv cs.AIagentsStructure Before Intelligence: Gating What Agentic Scientific Workflows Release
arXiv:2610.19507v1 Announce Type: new Abstract: An agentic scientific workflow can run to completion and still release wrong results: a silent numerical error, a stale input, or a defect in a shared upstream step can con…
- arXiv cs.AIresearchVLRLA: Deployment-Time Adaptation of Vision-Language-Action Models through In-Context Reinforcement Learning
arXiv:2610.19517v1 Announce Type: new Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-conditioned manipulation…
- arXiv cs.AIresearchRevisiting Triplet Contrastive Learning for 3D Shape Understanding
arXiv:2610.19519v1 Announce Type: new Abstract: In multi-modal 3D pre-training, aligning 3D shapes, their 2D image counterparts, and language descriptions has made tremendous progress. However, we find that supervision f…
- arXiv cs.AIagentsLabCompiler: A Framework for Verifiable Human-Machine Laboratory Execution from Imperfect Protocols
arXiv:2610.19550v1 Announce Type: new Abstract: Closing the loop of AI-driven science requires reliably translating natural-language protocols into executable laboratory workflows despite protocol defects and heterogeneo…
- arXiv cs.AIagents$\tau$-Emotion-Bench: Exposing the Interaction Fragility of LLM Agents through Real-World User Emotions
arXiv:2610.19560v1 Announce Type: new Abstract: In long-horizon tool-calling tasks, LLM agents can fail not only because of tool-use errors, but also because of ineffective interaction with users. Yet existing benchmarks…
- arXiv cs.AIresearchDivergence-Routed On-Policy Distillation for Language Models
arXiv:2610.19572v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers knowledge from a teacher model to a student along student-generated trajectories, typically by minimizing the reverse Kullback-Leible…
- arXiv cs.AIresearchWho's Behind the Text? Robust Model Authorship Attribution
arXiv:2610.19583v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used to generate text, their misuse has become a growing societal problem, with implications for academic misconduct, model…