AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAUGUstus: Autonomous Driving VLA Model with Unified Generation and Understanding
arXiv:2610.16985v1 Announce Type: cross Abstract: Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in long-tail scenario…
- arXiv cs.AIresearchTabGift: A Context-Efficient Foundation Model for Tabular Data Generation
arXiv:2610.16990v1 Announce Type: cross Abstract: Tabular data generation aims to synthesize realistic samples from limited observations while faithfully capturing the underlying data distribution. Tabular foundation mod…
- arXiv cs.AIresearchGoverning Copyright Responsibly in the Era of Generative AI
arXiv:2610.17002v1 Announce Type: cross Abstract: Large language models are trained on collections that may include scholarly works, while authors generally lack work-level information about whether and how their works w…
- arXiv cs.AIresearchMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation
arXiv:2610.17014v2 Announce Type: replace-cross Abstract: Functional brain connectome represents neural connectivity as a matrix of pairwise interactions between brain regions. Generation of functional connectomes is not…
- arXiv cs.AIresearchProbabilityBench: Model Evaluation and Calibration with Exact Ground-Truth Uncertainty
arXiv:2610.17016v1 Announce Type: cross Abstract: Evaluating model uncertainty on real-world data is challenging because each instance provides only a single observed label, leaving true conditional class probabilities u…
- arXiv cs.AIagentsCWE-bench: Refocusing Agentic Security from Exploitation to Defense
arXiv:2610.17020v1 Announce Type: cross Abstract: Cybersecurity evaluations of AI agents have focused largely on offense, yet a working exploit does not show that an agent can make software safe. An attacker needs to exp…
- arXiv cs.AIresearchSPLICE: Sparse Physics Library Identification and Compositional Expansion
arXiv:2610.17029v1 Announce Type: cross Abstract: Neural operator splitting composes a library of neural operators, one per physical mechanism, into zero-shot simulators of new equations. Existing approaches, however, re…
- arXiv cs.AIresearchGradient Routing Localizes and Removes Unintended Behaviors in RL
arXiv:2610.17062v1 Announce Type: cross Abstract: We propose a mitigation to reward hacking in reinforcement learning. Our setup involves a misspecified reward function that gives rise to unintended behavior, and a monit…
- arXiv cs.AIresearchSuperintelligence and the Triple Risk of an AI Race
arXiv:2610.17085v1 Announce Type: cross Abstract: On many estimates, artificial general intelligence (AGI) is likely to emerge within the next few decades or even sooner. Once it does, it may quickly surpass human intell…
- arXiv cs.AIagentsInteractive Navigation Beyond Reachability: Benchmark and Agentic Framework
arXiv:2610.17089v1 Announce Type: cross Abstract: Existing embodied navigation tasks commonly assume that traversability and object states remain fixed during an episode. Yet reaching a goal may require opening a door to…
- arXiv cs.AIresearchWhat the Machine Invented: Mining New Mathematical Instruments from OpenAI's October 2026 Release of AI-Generated Mathematics
arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository github.com/openai/mat…
- arXiv cs.AIresearchAIPOCH Open-Science: An Open-Source AI Research Workbench with Reproducible .science Packages
arXiv:2610.17110v1 Announce Type: cross Abstract: AI-assisted research leaves instructions, computations, artifact revisions and checks whose relationships matter when another researcher receives the work. We present AIP…
- arXiv cs.AIresearchCalibrated Typed Decisions for Entity, Relation, and Event Extraction
arXiv:2610.17113v1 Announce Type: cross Abstract: Information extraction models often perform well on the datasets they are trained on, but transferring to new domains and annotation guidelines remains challenging. Suppo…
- arXiv cs.AIresearchD-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control
arXiv:2610.17114v1 Announce Type: cross Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, held in network weigh…
- arXiv cs.AIresearchD2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones
arXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-SLMs) in general cap…
- arXiv cs.AIagentsWho is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents
arXiv:2610.17126v1 Announce Type: cross Abstract: The rapid proliferation of autonomous AI agents in decentralized ecosystems challenges existing identity paradigms. While human identity is traditionally anchored in biol…
- arXiv cs.AIresearchSonicWorld: Source-Centric Latent Dynamics for Spatial Audio Reasoning
arXiv:2610.17131v3 Announce Type: replace-cross Abstract: Dynamic spatial audio reasoning requires a model to associate changing acoustic observations with the correct source and recover its spatial state at a queried ti…
- arXiv cs.AIresearchForce-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation
arXiv:2610.17161v1 Announce Type: cross Abstract: Teleoperation is widely used to collect high-quality demonstrations for robot learning. Dexterous manipulation, however, requires coordinated control of motion and contac…
- arXiv cs.AIresearchGenerative Flow on Symbolic Abstractions for Embodiment Capability Discovery
arXiv:2610.17174v1 Announce Type: cross Abstract: Achieving complex, long-horizon robot behavior remains challenging because successful execution depends on skills grounded in a robot's physical affordances. Existing tra…
- arXiv cs.AIresearchFreeSolo: Linear-time Sparse Attention with Zero-Shot Length Extrapolation
arXiv:2610.17191v1 Announce Type: cross Abstract: Linear-time sequence models typically store long-context information in a recurrent state. A fixed-size state limits how much information can be stored, while hybrid arch…
- arXiv cs.AIagentsDeleting Code Without Losing Knowledge: Regenerative Software for Python Libraries
arXiv:2610.17197v1 Announce Type: cross Abstract: In the age of "Software 3.0", when a complete program can be rewritten in minutes by an agent, the traditional approach of relying on code as the sole source of truth bec…
- arXiv cs.AIresearchCompute-optimal data scaling for neural surrogates via multi-fidelity training
arXiv:2610.17221v1 Announce Type: cross Abstract: Neural surrogates for Partial Differential Equations (PDEs) are usually trained on synthetic data from numerical simulators. As models grow and scaling laws demand larger…
- arXiv cs.AIresearchFrom Conceptual EneMonIE to an Executable Backend: A Modular Architecture for Energy Information Extractionand Grounded Question Answering
arXiv:2610.17243v1 Announce Type: cross Abstract: The original EneMonIE proposal describes a Web-based semantic system for continuously monitoring energy trends through targeted information extraction from heterogeneous…
- arXiv cs.AIresearchMeasuring Learned Equivariance: An Information Theoretic Approach
arXiv:2610.17269v1 Announce Type: cross Abstract: Learning symmetries through data augmentation offers an alternative to architectural equivariance, but does not guarantee that a network respects those symmetries. Measur…
- arXiv cs.AIresearchPhase-Conditioned Affordance Fields for SE(3)-Equivariant Visuomotor Policies
arXiv:2610.17281v1 Announce Type: cross Abstract: SE(3)-equivariance provides a useful geometric inductive bias for visuomotor policies, encoding that actions covary with rigid transformations of the observation. However…
- arXiv cs.AIresearchStartLux-Decision: AutoThink Decision Models with Reinforcement Learning for Calibrated Deliberative Decisions
arXiv:2610.17309v2 Announce Type: replace-cross Abstract: We introduce StartLux-Decision, decision models from 0.8B to 27B parameters that combine efficient single-pass prediction with adaptive, confidence-guided reasoni…
- arXiv cs.AIresearchJoint Embedding with Dynamic Integration network (JEDI-net)
arXiv:2610.17314v1 Announce Type: cross Abstract: Deep learning has become the dominant form of machine learning due in part, to its ability to automatically engineer complex meta features from data. However, even deep l…
- arXiv cs.AIresearchThinking Outside the Bots: Human Ideas in AI's Semantic Blind Spots Are Not Inferior
arXiv:2610.17324v1 Announce Type: cross Abstract: AI-generated outputs are frequently perceived as highly creative, but also tend to be more similar to each other (homogenized) than human ideas. Does the human heterogene…
- arXiv cs.AIresearchOn the Statistical Mechanics of Attention
arXiv:2610.17347v1 Announce Type: cross Abstract: We revisit the statistical mechanics of Transformer attention via modern Hopfield models. We present a free-energy formalism to characterize parameter regimes and critica…
- arXiv cs.AIresearchMID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation
arXiv:2610.17354v2 Announce Type: replace-cross Abstract: Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which require e…
- arXiv cs.AIresearchclaimcheck: Measuring and Improving Specification Faithfulness
arXiv:2610.17358v1 Announce Type: cross Abstract: Formal verification proves that a program satisfies its specification, but says nothing about whether the specification captures what the author meant. As LLMs increasing…
- arXiv cs.AIresearchHASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation
arXiv:2610.17368v1 Announce Type: cross Abstract: Generative recommendation models have shown promising results by representing items as semantic IDs and generating these IDs autoregressively. We introduce an approach sh…
- arXiv cs.AIresearchMitigating Black-Box Score-Based Query Attacks via Gradient Confusion
arXiv:2610.17382v1 Announce Type: cross Abstract: Score-based black-box adversarial attacks pose a serious threat to deployed machine learning systems by exploiting repeated model queries to craft adversarial examples, r…
- arXiv cs.AIresearchCross-Market Meta-Learning for Electricity Price Forecasting
arXiv:2610.17387v1 Announce Type: cross Abstract: Day-ahead (DA) electricity price forecasting is usually posed per market, with a separate model fitted to each grid's own history. This caps accuracy: statistical and tre…
- arXiv cs.AIresearchLearning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting
arXiv:2610.17399v1 Announce Type: cross Abstract: Continuous monitoring of generative AI systems requires detecting distribution shifts in the unstructured data they ingest and generate. Existing monitoring methods typic…
- arXiv cs.AIresearchEvent-Centric Earthquake Monitoring with a Multi-Station Transformer
arXiv:2610.17404v1 Announce Type: cross Abstract: Earthquake catalogs underpin studies such as fault structure, earthquake processes and seismic hazard, and their value depends on being both complete and reliable. Machin…
- arXiv cs.AIresearchCross-View Time-Frequency Diffusion for Extreme-Aware Time-Series Generation
arXiv:2610.17407v2 Announce Type: replace-cross Abstract: Generating realistic time-series requires faithfully reproducing rare but high-impact extreme events. Existing approaches often rely on specialized representation…
- arXiv cs.AIresearchBottlenecked semantic compression by representation reconstruction
arXiv:2610.17412v1 Announce Type: cross Abstract: Vision Transformers incur high computational costs when processing long visual token sequences. Existing reduction methods typically rank tokens independently and discard…
- arXiv cs.AIagentsWhy Agentic Workflows Fail: A Taxonomy Derived from Literature and Empirical Data
arXiv:2610.17418v1 Announce Type: cross Abstract: Agentic workflows combine large language models with planning, memory, tools, execution environments, and iterative feedback. Their failures are difficult to diagnose bec…
- arXiv cs.AIagentsClearNav: Perception-Aligned Quadrotor Flight Using Differential-Physics
arXiv:2610.17419v1 Announce Type: cross Abstract: Autonomous quadrotor flight in cluttered environment is an key capability for tasks like inspection and search. Navigation policies trained in simulation and transferred…
- arXiv cs.AIresearchOn Making $\mathrm{SE}(2)$-Invariant Networks Optimal
arXiv:2610.17424v1 Announce Type: cross Abstract: Respecting a-priori known symmetries of underlying data is a key principle in designing efficient neural architectures. Convolutional neural networks are a canonical exam…
- arXiv cs.AIresearchReinforcement Learning In Partially Verifiable Environments for Colon Cancer Treatment Planning
arXiv:2610.17426v1 Announce Type: cross Abstract: Clinical decision-making is a sequential process of information collection, clinical inference, and forecasting under partial observability, often without a uniquely corr…
- arXiv cs.AIresearchWorld-T3: Test-Time Training as Persistent Memory for Real-Time Video World Models
arXiv:2610.17434v1 Announce Type: cross Abstract: Recent advances in video world models have enabled plausible interactive environments, yet long-horizon generation places a fundamental demand on visual memory: the previ…
- arXiv cs.AIresearchKnow-Thy-Not: Training-Free Targeted Negation in Dual-Encoder Vision-Language Models
arXiv:2610.17440v1 Announce Type: cross Abstract: Dual-encoder vision-language models systematically fail at negation, scoring ''a cat without a dog'' nearly identically to ''a cat with a dog.'' We show that this failure…
- arXiv cs.AIagentsThe belief-action gap in language model agents
arXiv:2610.17444v1 Announce Type: cross Abstract: Language model (LM) agents can fail for different reasons, requiring different explanations and interventions. We study how state beliefs, action values, and action prefe…
- arXiv cs.AIresearchCompositional RL: Evaluating and Training LLMs for Collaborative Reasoning
arXiv:2610.17456v1 Announce Type: cross Abstract: Language models are often evaluated alone but increasingly deployed together, routed between, made to debate, ensembled, or collaboratively trained. For a model inside a…
- arXiv cs.AIresearchAssessing the Performance of AI Models in Misinformation Detection Using Predefined Social Noise Constructs
arXiv:2610.17469v1 Announce Type: cross Abstract: Social media platforms generate vast volumes of user-generated content that often obscure meaningful discourse, a phenomenon conceptualized as social noise. While existin…
- arXiv cs.AIresearchVeriPIE: Checkable Query Plans and Evidence-Guided Selection for Text-to-SQL
arXiv:2610.17493v1 Announce Type: cross Abstract: Financial Artificial Intelligence (AI) governance and model risk management (MRM) emphasize independent validation, transparency, and effective challenge of AI-generated…
- arXiv cs.AIagentsFoundation Models for Event Prediction Across Heterogeneous Event Logs
arXiv:2610.17503v1 Announce Type: cross Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational systems. Yet event logs…
- arXiv cs.AIresearchYUBI-Real2Sim: 3DGS Scene Verification for Reliable Policy Evaluation
arXiv:2610.17521v1 Announce Type: cross Abstract: Evaluating VLA policies on real robots is costly, time-consuming, and difficult to reproduce, making real-to-sim simulation essential for scalable evaluation. While 3D Ga…