AI news archive.
19,856 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchCryoAtlas: A Large Curated Dataset and Unified Benchmark for Cryo-EM Atomic Model Building
arXiv:2610.41411v1 Announce Type: new Abstract: Deep learning has accelerated automated atomic model building from cryo-EM maps, yet progress remains limited by the lack of large, high-quality datasets and standardized e…
- arXiv cs.AIagentsEvidence-Guided Recovery for AI Agents with Ambiguous Tool Outcomes and Partial Execution
arXiv:2610.41453v1 Announce Type: new Abstract: Tool timeouts can leave AI agents facing ambiguous tool outcomes and partial execution: an action may have failed, committed or remained in flight while other workflow step…
- arXiv cs.AIagentsEvoMCP: Co-evolving MCP agents and training data
arXiv:2610.41479v1 Announce Type: new Abstract: Supervised fine-tuning of Model Context Protocol (MCP) agents is typically conducted on a static data distribution, which fails to adapt to the student's evolving capabilit…
- arXiv cs.AIresearchMulti-Test Nation Bias Benchmarking of LLMs with Explicit Unbiased Baselines
arXiv:2610.41486v1 Announce Type: new Abstract: While prior work has highlighted that systematic nation-level bias in large language models (LLMs) can pose operational risks for international relations (IR) applications,…
- arXiv cs.AIresearchSpecification-Guided Generation for Large Language Models
arXiv:2610.41511v1 Announce Type: new Abstract: Large language models (LLMs) can generate structured outputs, but existing constrained-decoding methods mainly enforce syntax and cannot directly enforce satisfaction of a…
- arXiv cs.AIagentsVerify--Backtrack Loop: Structured Precondition Recovery for Long-Horizon Language Agents
arXiv:2610.41564v1 Announce Type: new Abstract: Language agents increasingly tackle long-horizon tasks in interactive environments, where actions often depend on latent preconditions. The core difficulty is not trajector…
- arXiv cs.AIresearchConnectivity-Aware Client Selection in Decentralized Federated Learning
arXiv:2610.41570v1 Announce Type: new Abstract: Decentralized federated learning (DFL) has emerged as a scalable alternative to centralized federated learning, removing the single point of failure and communication bottl…
- arXiv cs.AIresearchPatch-Based Deep Kernel Learning for Data Assimilation and Bias Correction with Extremely Sparse Observations
arXiv:2610.41596v1 Announce Type: new Abstract: Data Assimilation (DA) reconstructs the state of a spatio-temporal system by combining sensor observations with the output of a numerical model. Since model states are high…
- arXiv cs.AIagentsReal Computation or Merely Naming? A Pre-Registered Mechanism Audit of 25 Cognitive-Architecture Modules in an LLM-Based Agent System
arXiv:2610.41604v1 Announce Type: new Abstract: Agent systems built on local large language models are increasingly marketed through the vocabulary of cognitive architecture: modules named global workspace, theory of min…
- arXiv cs.AIresearchWhat Should LLMs Forget: Reinforcement Unlearning of Knowledge Associations
arXiv:2610.41616v1 Announce Type: new Abstract: Large language models (LLMs) acquire extensive factual knowledge during pre-training, which may include sensitive, private, or copyrighted information, motivating the devel…
- arXiv cs.AIagentsChance-Constrained Inspection Viewpoint Sequencing for On-Orbit Servicing via Safe Reinforcement Learning
arXiv:2610.41639v1 Announce Type: new Abstract: Autonomous inspection of a target spacecraft is typically the initial step in on-orbit servicing. Planning close-proximity observation viewpoints involves a complex combina…
- arXiv cs.AIresearchRisk-Sensitive Mission Planning for Multi-Target On-Orbit Inspection via Distributional Reinforcement Learning
arXiv:2610.41647v1 Announce Type: new Abstract: Multi-target on-orbit servicing missions require planning tools that can adapt to evolving operational conditions while accounting for the outcome variability inherent to s…
- arXiv cs.AIresearchBreaking Information Islands in Sparse Tuning via Small-World Connectivity
arXiv:2610.41665v1 Announce Type: new Abstract: Sparse tuning is widely used to adapt large language models due to its parameter efficiency. However, its effectiveness depends not only on the number of trainable paramete…
- arXiv cs.AIresearchRadial Kernel Attention for Long-Range Modeling in Polymer Machine Learning Force Fields
arXiv:2610.41675v1 Announce Type: new Abstract: We introduce Radial Kernel Attention (RKA) for long-range modeling in polymer machine learning force fields. Local neighbor graphs constrain communication across polymer ch…
- arXiv cs.AIagentsTSBPO: Tree-Structured Branching for Policy Optimization in Interactive Language Agents
arXiv:2610.41697v1 Announce Type: new Abstract: Training interactive language agents from terminal outcomes poses three coupled problems: which task and state continuations to sample, how to assign delayed feedback to de…
- arXiv cs.AIresearchAdvancing Clinical Trial Outcome Prediction with Domain-Specific Large Language Models
arXiv:2610.41710v1 Announce Type: new Abstract: Clinical trial failures are a major barrier to efficient drug development, incurring substantial costs and delaying patient access to effective therapies. Structured approa…
- arXiv cs.AIresearchMultimodal In-Context Learning with Explicit Rule Induction
arXiv:2610.41754v1 Announce Type: new Abstract: A central challenge in multimodal in-context learning (MICL) arises from tasks that are ill-defined without context and require uncovering the underlying rules from demonst…
- arXiv cs.AIagentsClinical-Protocol-Aware Cyber Resilience for Connected Clinical Technologies Under AI-Enabled Adversarial Conditions
arXiv:2610.41784v1 Announce Type: new Abstract: Healthcare increasingly relies on connected medical devices, clinical information systems, cloud services, and distributed-care technologies, creating cybersecurity risks a…
- arXiv cs.AIresearchWhose Values, Which Contexts, and What Signals? Grounding Cultural Value Alignment with Re3Culture
arXiv:2610.41793v1 Announce Type: new Abstract: Cultural value alignment requires not only model optimization but also a well-specified target grounded in real-human evidence. Yet how such targets should be grounded in h…
- arXiv cs.AIresearchRECAST: REconstruction of Chain-of-Thought via Auditable Structured Traces
arXiv:2610.41813v1 Announce Type: new Abstract: Large closed-source reasoning models expose only their final answers. The intermediate reasoning that produces those answers is hidden behind API surfaces, tool-call polici…
- arXiv cs.AIresearchReuScope: Auditing Data Reuse and Evaluation Sensitivity in Capsule Vision 2024
arXiv:2610.41835v1 Announce Type: new Abstract: We develop ReuScope, a protocol for auditing data reuse and evaluation sensitivity, using Capsule Vision 2024 as a case study. It combines measurements of data relationship…
- arXiv cs.AIresearchDynamical Memory Transformer: Selective Recurrent Memories with Constant Cost Attention
arXiv:2610.41850v1 Announce Type: new Abstract: Transformers retain an explicit history of the sequence, allowing attention to directly retrieve past representations. However, the size of the KV-Cache and the cost of a n…
- arXiv cs.AIagentsLearning to Interact and Direct: Co-Evolving Video Director Agents
arXiv:2610.41865v1 Announce Type: new Abstract: Video director agents orchestrate multistage production to realize users' creative visions. Emerging research on their self-evolution advances screenplay planning effective…
- arXiv cs.AIresearchFuzzy selective state model for forecasting the dynamics of consumer preferences
arXiv:2610.41879v1 Announce Type: new Abstract: We consider forecasting the dynamics of consumer preferences of retail chain customers. A customer's preference is described by a triangular fuzzy number. The evolution of…
- arXiv cs.AIresearchAutomated Keyword Generation Using LLMs in a High-Volume Data Virtualization Service
arXiv:2610.41893v1 Announce Type: new Abstract: In modern data infrastructure, a data virtualization service (DVS) allows users to create many versions of source datasets for different processing tasks. For example, a mu…
- arXiv cs.AIresearchUsing Machine Learning to Measure Self-Efficacy Belief Through Learners' Interaction Traces in Technology-Enhanced Learning
arXiv:2610.41900v1 Announce Type: new Abstract: Self-efficacy beliefs play a critical role in learners' performance, academic choices, and, more broadly, in their future career trajectories. As Technology-Enhanced Learni…
- arXiv cs.AIresearchReX-GG: a LLM Ensemble Pipeline for Relation-extraction and Graph Generation
arXiv:2610.41901v1 Announce Type: new Abstract: Current LLM ensemble frameworks focus on multi-step setups with additional modules for answer ranking, often opting for token and span analysis rather than structured outpu…
- arXiv cs.AIagentsStructure-Aware Skill Retrieval and Arbitration for Optimization Modeling
arXiv:2610.41909v1 Announce Type: new Abstract: Large Language Models (LLMs) can turn natural-language optimization tasks into solver-checked answers, but current agents remain brittle under narrative rewrites and often…
- arXiv cs.AIresearchSensorium: An Open-Source Multimodal Data Collection and Curation Library for Embodied Surgical AI
arXiv:2610.41946v1 Announce Type: new Abstract: Embodied surgical AI requires reliable multimodal data, yet surgical data collection remains costly, difficult to repeat, and strongly dependent on the hardware setup. We p…
- arXiv cs.AIresearchOptimizing Stochastic Policy Geometry for Few-Step Flow Reinforcement Learning
arXiv:2610.41949v1 Announce Type: new Abstract: Few-step flow models generate samples through a handful of large denoising transitions. Applying GRPO to such models requires introducing stochasticity into the denoising t…
- arXiv cs.AIresearchPrune Gradually, Adapt Sparsely: Efficient Pruning of Large Language Models at Extreme Sparsity
arXiv:2610.41968v1 Announce Type: new Abstract: Weight pruning can reduce the storage and inference cost of large language models (LLMs), but preserving quality at high sparsity levels remains challenging. Existing metho…
- arXiv cs.AIresearchWhen Does Test-Time Search Help World Action Models? An Empirical Audit of Candidate Selection and Simulator Integrity
arXiv:2610.41970v1 Announce Type: new Abstract: World-action models increasingly apply test-time scaling, spending extra inference computation on candidate selection and adaptive allocation to improve control. Such gains…
- arXiv cs.AIresearchID2Pattern: Pretraining Generalizable Identity Behavior Patterns for Transaction Risk Foundation Models
arXiv:2610.41988v1 Announce Type: new Abstract: Large-scale behavioral pretraining offers a promising route to generalizable representations in online payment systems. However, high-cardinality identity fields such as ca…
- arXiv cs.AIresearchDAMI: Dual-Axis Memory Initialization for Enhanced Long-Context Retrieval in Gated Linear Attention
arXiv:2610.41994v1 Announce Type: new Abstract: Linear attention scales linearly with sequence length, but its finite-state memory can limit long-context retrieval. In gated linear recurrences, memory retention depends o…
- arXiv cs.AIagentsTradeWar: A Benchmark for Execution-Grounded Trade Negotiation with Adaptive LLM Agents
arXiv:2610.42004v1 Announce Type: new Abstract: Multi-turn negotiation remains a challenging problem for large language model (LLM) agents. While LLMs can conduct natural-language dialogue, existing benchmarks predominan…
- arXiv cs.AIresearchSame Question, Different Answers: Auditing Persona-Dependent Variation in Six LLMs on Smoking-Cessation Advice
arXiv:2610.42039v1 Announce Type: new Abstract: Hundreds of millions of people now ask large language model (LLM) chatbots for health advice, which raises a question that is simple to pose and hard to answer: does everyo…
- arXiv cs.AIresearchThe Knowledge Layer Model (KLM): Evidence-Visible AI Output, Routing Diagnostics, and Negative Results
arXiv:2610.42066v1 Announce Type: new Abstract: AI answers require more than apparent correctness: reviewers need to inspect their recorded basis. We introduce the Knowledge Layer Model (KLM), an open, implementation-neu…
- arXiv cs.AIresearchCausalWAM: Learning the Causes of Actions in World Action Models
arXiv:2610.42096v1 Announce Type: new Abstract: World action models (WAMs) learn latent variables from observations and use these to both predict the evolution of the scene and to generate actions. The prediction has to…
- arXiv cs.AIresearchACCT: Asymmetric Cross-LLM Context Transfer
arXiv:2610.42116v1 Announce Type: new Abstract: In real-world deployments, large language model (LLM) systems are increasingly evolving from single-model invocation toward heterogeneous deployments in which different mod…
- arXiv cs.AIagentsLatent Sparse Attention: Towards Subquadratic Ultra-Long Context Attention
arXiv:2610.42147v1 Announce Type: new Abstract: Agentic workflows are increasingly shifting towards long-horizon tasks, such as open-ended scientific work, where models benefit from long context windows. However, at ultr…
- arXiv cs.AIresearchHear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning
arXiv:2506.20651v1 Announce Type: cross Abstract: Recent work has shown that gradient updates in federated learning (FL) can unintentionally reveal sensitive information about a client's local data. This risk becomes sig…
- arXiv cs.AIresearchLeaner Training, Lower Leakage: Revisiting Memorization in LLM Fine-Tuning with LoRA
arXiv:2506.20856v1 Announce Type: cross Abstract: Memorization in large language models (LLMs) makes them vulnerable to data extraction attacks. While pre-training memorization has been extensively studied, fewer works h…
- arXiv cs.AIresearchRecycle only when you have to!
arXiv:2610.40665v1 Announce Type: cross Abstract: AlphaFold 3-like models (e.g., Boltz, Protenix, etc.) have pushed the frontier of protein binder design. This architecture is used both for the generation of binder candi…
- arXiv cs.AIresearchCausalGrade: Evidence-Guided Causal Graph Scoring with Jev
arXiv:2610.40692v1 Announce Type: cross Abstract: Evaluating the structural quality of candidate causal graphs when the true causal structure is unknown is an important problem in applying causal discovery results. This…
- arXiv cs.AIagentsPrivacyFlow: Privacy in AI Agents through Information Flow Analysis and Consequence-Aware Risk Management
arXiv:2610.40714v1 Announce Type: cross Abstract: Autonomous LLM agents executing multi-step workflows over personal data often misalign with user privacy expectations and leak sensitive, out-of-context information. Alth…
- arXiv cs.AIagentsCharacterizing LLM Agent Behaviors in Module Shadowing Environments
arXiv:2610.40716v1 Announce Type: cross Abstract: LLM agents operating in untrusted workspaces face the risk of untrusted code execution during routine tasks, yet final reports and workspace states alone cannot reliably…
- arXiv cs.AIagentsMetaVul: Agentic Harness Discovery for Vulnerability Detection
arXiv:2610.40721v1 Announce Type: cross Abstract: LLM agents are increasingly used to automate vulnerability detection, but reliable detection is challenging because agents must distinguish subtle, security-relevant fixe…
- arXiv cs.AIresearchBayesian Distribution System State Estimation with Flow Matching
arXiv:2610.40728v1 Announce Type: cross Abstract: Medium-voltage feeders have few real-time measurements, so distribution system state estimation (DSSE) rests on pseudo-measurements of the secondary substations, a prior…
- arXiv cs.AIresearchRiskyPy: Toward Model-Calibrated Prompt Generation for Joint Security and Functionality Evaluation of LLM-Generated Code
arXiv:2610.40735v1 Announce Type: cross Abstract: Evaluating approaches that improve the security of LLM code generation requires datasets that jointly assess security and functionality and remain adapted to the capabili…
- arXiv cs.AIresearchCLIC: Closed-Loop Intent Consistency for Securing LLM-Driven Control in Open RAN
arXiv:2610.40744v1 Announce Type: cross Abstract: With the progressive capabilities of large language models (LLMs), researchers are finding ways to integrate them into the control loops of Open Radio Access Network (O-R…