AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchArchitectural Sampling: Test-Time Scaling via Computational Diversity in Frozen Vision-Language Models
arXiv:2610.01687v1 Announce Type: cross Abstract: Test-time scaling often seeks better answers by sampling multiple responses from a frozen model, yet conventional temperature sampling generates every candidate along the…
- arXiv cs.AIresearchArchitecture Without an Architect? Global Governance of Artificial Intelligence in a Divided World
arXiv:2610.01716v1 Announce Type: cross Abstract: Artificial intelligence presents an unusually difficult problem for global governance. The technology develops rapidly, crosses borders easily, and is shaped by actors wh…
- arXiv cs.AIresearchRemoving spurious minima for planar features by skip connections
arXiv:2610.01728v2 Announce Type: replace-cross Abstract: Understanding loss landscapes is central to explaining neural-network training, yet their structure remains only partially understood even in simple models. We st…
- arXiv cs.AIresearchCog-VADU: A Training-Free Cognitive Reasoning Framework for Video Anomaly Detection and Understanding
arXiv:2610.01754v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) aims to temporally localize abnormal events in videos. Most existing approaches rely on dataset-specific training and curated annotations, l…
- arXiv cs.AIagentsSoK: Decentralized Agent Economic Infrastructure
arXiv:2610.01756v1 Announce Type: cross Abstract: Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately. This creates a simple problem: a workflow can loo…
- arXiv cs.AIresearchCODesign: Consistency from Data to Trajectory in All-Atom Protein Binder Co-Design
arXiv:2610.01773v1 Announce Type: cross Abstract: The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequence folds into its int…
- arXiv cs.AIresearchVETO: Video Efficient Token Optimization for Vision Language Models
arXiv:2610.01785v1 Announce Type: cross Abstract: Processing long videos with Vision-Language Models (VLMs) is bottlenecked by the quadratic cost of visual tokens, making long-form inference prohibitively expensive. Whil…
- arXiv cs.AIresearchiADD: Improving Alignment and Diversity in Diffusion Policy Optimization
arXiv:2610.01789v1 Announce Type: cross Abstract: Reinforcement learning based post training of diffusion models, such as Denoising Diffusion Policy Optimization (DDPO), optimizes a reverse diffusion process under a rewa…
- arXiv cs.AIagentsToken Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunities
arXiv:2610.01826v1 Announce Type: cross Abstract: Collaborative embodied artificial intelligence (CEAI) enables multiple physical agents to perceive, reason, and act cooperatively in dynamic environments. Effective commu…
- arXiv cs.AIresearchDetecting Inconsistencies in Model Specifications with LLM-as-Verifier Reasoning
arXiv:2610.01847v1 Announce Type: cross Abstract: Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation. Yet these specifications…
- arXiv cs.AIresearchFrom Isolated Feature to Orbits: Discovering Music Concepts via Multi-SAE Alignment
arXiv:2610.01864v1 Announce Type: cross Abstract: How can we understand what a music foundation model has learned \textit{internally}? Most interpretability approaches, such as probing and Sparse Autoencoders (SAEs), foc…
- arXiv cs.AIresearchWalking the Embedding Space: Datastore Extraction from Multimodal RAG
arXiv:2610.01871v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (MRAG) has emerged as a reliable and cost-effective technique of grounding the generative capabilities of Multimodal Large Langu…
- arXiv cs.AIresearchFrom Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures
arXiv:2610.01872v1 Announce Type: cross Abstract: While the literature on blockchain-assisted intrusion detection and prevention systems (IDS/IPS) for Internet of Things (IoT) and Industrial Internet of Things (IIoT) net…
- arXiv cs.AIagentsFlowing Faster to Coordinate: One-Step Online Multi-Agent Flow Policies
arXiv:2610.01882v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment. Developing MARL poli…
- arXiv cs.AIresearchUnsupervised Domain Adaptation for Enhanced Radiometer Image Precipitation Estimation using Conditional Flow Matching
arXiv:2610.01890v1 Announce Type: cross Abstract: Deep generative networks have recently achieved unprecedented performance in precise image and video editing using sophisticated textual prompts. However, the effectivene…
- arXiv cs.AIagentsSelection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents
arXiv:2610.01892v2 Announce Type: replace-cross Abstract: Multimodal agents commonly generate free-form reasoning before each action. For small models, limited model capacity can result in lengthy reasoning that provides…
- arXiv cs.AIresearchA Structured State Space Sequence Model for Multi-Class Classification of Malware
arXiv:2610.01893v1 Announce Type: cross Abstract: By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, healthcare, agricultur…
- arXiv cs.AIresearchAsynchronous LLM Post-Training: Group-Mass Capping and Convergence Analysis
arXiv:2610.01896v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earlier policies. Theore…
- arXiv cs.AIresearchMoLE: Mixture of Latent Experts for Complementary Visual Reasoning
arXiv:2610.01917v2 Announce Type: replace-cross Abstract: Latent visual reasoning equips vision--language models with continuous intermediate states that can process visual evidence without explicit textual reasoning tra…
- arXiv cs.AIresearchCross-Lingual Alignment for Decoder-Only Models using MoE Routers
arXiv:2610.01921v2 Announce Type: replace-cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is not possible…
- arXiv cs.AIresearchA rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined
arXiv:2610.01938v2 Announce Type: replace-cross Abstract: Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integrating and upd…
- arXiv cs.AIresearchA Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders
arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are typically launched th…
- arXiv cs.AIagentsMem++: Non-Destructive Memory for Long-Term Organizational LLM Agents
arXiv:2610.02002v1 Announce Type: cross Abstract: Large Language Model (LLM) agents now take part in organizational work, where many authors record decisions across documents over months. Because a revised decision arriv…
- arXiv cs.AIresearchExploring Weaknesses of Generative Image Watermarks against Latent Frequency Masking
arXiv:2610.02010v1 Announce Type: cross Abstract: Invisible watermarking has become a central tool for tracing AI-generated images, but its robustness against adaptive removal attacks remains an open security question. W…
- arXiv cs.AIresearchOn Language Drift during RLVR Post-Training
arXiv:2610.02015v1 Announce Type: cross Abstract: Recent advances in LLM reasoning models---driven primarily by the paradigm of post-training via reinforcement learning with verifiable reward (RLVR)---have enabled them t…
- arXiv cs.AIresearchTask-Adaptive Grounded 3D-Programmers Using 2D VLMs
arXiv:2610.02021v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) exhibit remarkable generalization and reasoning abilities, yet 3D understanding in these models is limited by data scale, training di…
- arXiv cs.AIresearchCARM: Cancellation-Aware Response Masking for LLM Reinforcement Learning
arXiv:2610.02039v1 Announce Type: cross Abstract: Recent years have witnessed the rapid adoption of reinforcement learning (RL) in large language model (LLM) post-training, with substantial gains in mathematical reasonin…
- arXiv cs.AIresearchDistributionally Robust Schr\"odinger Bridge
arXiv:2610.02043v1 Announce Type: cross Abstract: Schr\"odinger bridge (SB) learns stochastic transport between prescribed initial and target distributions. When the initial distribution shifts at test time, the learned…
- arXiv cs.AIresearchHumanoidToolBench: Benchmarking Humanoid Tool Use from Selection to Mobile Execution
arXiv:2610.02089v1 Announce Type: cross Abstract: As robotic hardware and learning methods advance, humanoids need tools to perform tasks beyond their inherent physical limits. Successful tool use requires selecting a su…
- arXiv cs.AIresearchGeoLatent: Geometry-Guided Latent Structuring with Routed Optimization for 3D Reasoning
arXiv:2610.02091v1 Announce Type: cross Abstract: Despite progress in vision-language models, 3D spatial reasoning from 2D images remains challenging. Text-based methods describe intermediate geometry with discrete token…
- arXiv cs.AIresearchScalable, Transferable Meta-network for Data Selection Requires a Different Loss (and Why the Obvious Choice is Problematic)
arXiv:2610.02092v1 Announce Type: cross Abstract: Data selection is critical for training large language models on massive and heterogeneous corpora. Meta-learning for Training-data Selection offers a principled alternat…
- arXiv cs.AIresearchWhere-OPD: Spatially Guided On-Policy Self-Distillation of MLLMs with Synthetic Scenes
arXiv:2610.02117v1 Announce Type: cross Abstract: On-policy self-distillation has recently emerged as an effective approach for improving language-model reasoning by supervising students with a frozen or EMA version of t…
- arXiv cs.AIagentsArgo-Bench: Evaluating Data Agents on Enterprise-Scale Workflows
arXiv:2610.02122v1 Announce Type: cross Abstract: Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statistical analyses, and acting on the results. Establis…
- arXiv cs.AIresearchLocal Support Learning
arXiv:2610.02126v1 Announce Type: cross Abstract: We explore catastrophic forgetting in the context of large pre-trained models. By considering forgetting as a geometric problem in the input space of each weight matrix,…
- arXiv cs.AIresearchMIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI
arXiv:2610.02136v1 Announce Type: cross Abstract: Unsupervised anomaly detection (UAD) methods for brain MRI are ranked by a single score, yet that score rests on choices that are rarely reported: how each anomaly map is…
- arXiv cs.AIresearchFinetuning with Sampling: SFT Learns Better Than You Think
arXiv:2610.02140v1 Announce Type: cross Abstract: Introducing new capabilities to frontier models has long been the goal of posttraining, which predominantly employs supervised finetuning (SFT) and reinforcement learning…
- arXiv cs.AIagentsFrom Knowledge Access to Source Learning: Developing Source-Specific Competence
arXiv:2610.02150v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods improve how source co…
- arXiv cs.AIresearchDuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication
arXiv:2610.02161v1 Announce Type: cross Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progress has focused on sin…
- arXiv cs.AIresearchWatch, Infer, Coordinate: Inferring Robot Partner Constraints for Zero-Shot Coordination
arXiv:2610.02170v1 Announce Type: cross Abstract: Robots operating in the physical world will increasingly need to coordinate with other robots, particularly in manipulation tasks where an object may be too large or heav…
- arXiv cs.AIresearchGenerative Cinematographer: Composing Camera and Object Motion in 3D
arXiv:2610.02180v1 Announce Type: cross Abstract: Current controllable video generation systems often rely on 2D motion trajectories or sparse drag signals for object motion. These controls are ambiguous because the same…
- arXiv cs.AIresearchSoftServe: A Scalable Quasi-Newton Method for Deep Learning
arXiv:2610.02182v1 Announce Type: cross Abstract: Quasi-Newton (QN) methods have long been among the most effective methods for large-scale unconstrained convex optimization. Two obstacles have limited their use in deep…
- arXiv cs.AIresearchHigher-Order Molecular Grammars for Generative and Foundation Models in Chemistry
arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly encode higher-order…
- arXiv cs.AIresearchDMAD: Distribution Matching as Adversarial Distillation for Fast Visual Generation
arXiv:2610.02188v2 Announce Type: replace-cross Abstract: Distribution Matching Distillation (DMD) trains a few-step student from the difference between separately estimated target and student scores, so it must keep an…
- arXiv cs.AIresearchHierarchical Continuous Diffusion Language Models
arXiv:2610.02193v1 Announce Type: cross Abstract: Discrete diffusion language models offer a compelling alternative to autoregressive generation for tasks demanding bidirectional reasoning and global constraint satisfact…
- arXiv cs.AIresearchFERPO: Forward Entropy-Regularized Policy Optimization
arXiv:2610.02198v2 Announce Type: replace-cross Abstract: Several state-of-the-art methods for online reinforcement learning in continuous control improve policies using action gradients of a learned critic. However, cri…
- arXiv cs.AIresearchSILSA: Sliding-Window Slice Latents for Topology-Preserving High-Resolution 3D Generation
arXiv:2610.02201v1 Announce Type: cross Abstract: High-resolution 3D generation increasingly relies on voxel latents and multi-stage pipelines that first predict active structure and then synthesize local geometry. While…
- arXiv cs.AIagentsReconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents
arXiv:2610.02204v1 Announce Type: cross Abstract: Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integrate perception with…
- arXiv cs.AIagentsKaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards
arXiv:2610.02206v1 Announce Type: cross Abstract: LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existing evaluations focus…
- arXiv cs.AIresearchOne Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars
arXiv:2610.02207v1 Announce Type: cross Abstract: 3D Gaussian avatars support fast rendering, however, their real-time animation is often challenged by the costly neural inference. We address this bottleneck and show tha…
- arXiv cs.AIresearchMulti-Sensor Fusion for UAV Classification Based on Feature Maps of Image and Radar Data
arXiv:2410.16089v3 Announce Type: replace Abstract: The cost, flexibility, and efficiency of modern UAVs make them attractive across many applications, but their proliferation has driven a rising number of malicious or a…