AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchRoboTalk: Learning Multi-Robot Communication and Coordination from Multimodal Demonstrations
arXiv:2609.23997v2 Announce Type: replace-cross Abstract: Multi-robot collaboration could enable more efficient and scalable solutions to complex robotic tasks, but collaboration under partial observability remains chall…
- arXiv cs.AIresearchMisaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models
arXiv:2609.23999v3 Announce Type: replace-cross Abstract: How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood. We investigated how four open-weight LLMs (Qwen-2.…
- arXiv cs.AIresearchInterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection
arXiv:2609.24026v1 Announce Type: cross Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object detection. Existing me…
- arXiv cs.AIresearchMECT: Mixture of Experts with CNN-Transformer Network for Speaker verification
arXiv:2609.24061v1 Announce Type: cross Abstract: In this paper, we propose MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone with optimized block s…
- arXiv cs.AIresearchFrom Content Generation to Learning Support: Pedagogy-Guided Generative Video Tutors for STEM Learning
arXiv:2609.24083v1 Announce Type: cross Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than supporting learning.…
- arXiv cs.AIresearchFrom Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models
arXiv:2609.24084v1 Announce Type: cross Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification difficult. Existing bla…
- arXiv cs.AIresearchFlashBoB: I/O-Efficient Exact Backward-over-Backward for Softmax Attention
arXiv:2609.24089v2 Announce Type: replace-cross Abstract: Transformer models built on the attention mechanism have become a central building block in modern deep learning, yet softmax attention remains a major bottleneck…
- arXiv cs.AIagentsWidgetVA: A Widget-Centric Framework and Benchmark for Agentic Visual Analytics
arXiv:2609.24094v1 Announce Type: cross Abstract: Visual analytics (VA) enables sensemaking through interactive visualization, but effective analysis often requires experts to translate high-level intents into long seque…
- arXiv cs.AIagentsReinforcement Learning under State and Outcome Uncertainty: A Foundational Distributional Perspective
arXiv:2609.24103v1 Announce Type: cross Abstract: In many real-world planning tasks, agents must tackle uncertainty about the environment's state and variability in the outcomes of any chosen policy. We address both form…
- arXiv cs.AIresearchActiveArena: Benchmarking and Understanding Active Perception in Robotic Manipulation
arXiv:2609.24124v2 Announce Type: replace-cross Abstract: Active perception and manipulation are crucial for robots to interact with complex scenes. Existing benchmarks struggle to evaluate how robots effectively acquire…
- arXiv cs.AIagentsAction-Slot: Structured Action-Centric Representation Learning for Multi-Agent Atomic Activity Understanding
arXiv:2609.24127v1 Announce Type: cross Abstract: Atomic activity understanding aims to recognize and localize structured traffic behaviors that jointly encode motion patterns and their grounding in road topology. Unlike…
- arXiv cs.AIagentsData Agents: Agentic Data Systems
arXiv:2609.24137v1 Announce Type: cross Abstract: Traditional data systems face profound limitations in the AI era, relying on human-crafted pipelines, lacking semantic understanding of heterogeneous data, and operating…
- arXiv cs.AIresearchSTAR: Scene- and Task-Aware 4D Radar Preprocessing Towards End-to-End Cognitive Radar
arXiv:2609.24151v1 Announce Type: cross Abstract: Four-dimensional (4D) Radar has emerged as a key sensor for environmental perception, providing range, azimuth, elevation, and Doppler measurements while remaining robust…
- arXiv cs.AIresearchGraded-Relevance Composed Multimodal Retrieval for E-commerce Visual Search at Scale
arXiv:2609.24152v1 Announce Type: cross Abstract: Visual search on large e-commerce catalogs must serve both "similarity" queries that ask for items resembling an uploaded image and "modifier" queries that comprise an im…
- arXiv cs.AIresearchTAC-Time: Texts as Channels For Multimodal Time Series Forecasting
arXiv:2609.24156v1 Announce Type: cross Abstract: Most existing time series forecasting methods rely solely on numerical observations, overlooking rich contextual information from auxiliary texts. Recent multimodal appro…
- arXiv cs.AIagentsMCP-GRANITE Benchmark: GRANularity Interface TEsting for MCP-Based LLM Agents
arXiv:2609.24161v1 Announce Type: cross Abstract: As LLM agents increasingly interact with external tools through standardized protocols such as MCP, tool-interface design becomes a critical yet underexplored factor. How…
- arXiv cs.AIresearchOpinion Leader Dynamics: How Sparse Attention Shapes Token Clustering
arXiv:2609.24202v1 Announce Type: cross Abstract: Sparse attention reduces the quadratic cost of global self-attention while retaining strong empirical performance, but how its restricted interactions shape the evolution…
- arXiv cs.AIresearchMemory vs. Context? Influential Factors of Factual Recall in Language Models
arXiv:2609.24238v1 Announce Type: cross Abstract: We reproduce and stress-test the work of Yu et al. (2023), who characterize how language models (LMs) arbitrate between memorized knowledge and contradictory in-context s…
- arXiv cs.AIresearchHessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models
arXiv:2609.24241v1 Announce Type: cross Abstract: Uncovering latent variables and their causal relations from observed data is a fundamental yet challenging problem. Existing methods often rely on restrictive assumptions…
- arXiv cs.AIresearchTaramandal-GPT: Enhancing Astrodynamics Problem-Solving with Knowledge Retrieval and Structured Thinking
arXiv:2609.24246v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable progress in natural language understanding, yet their effectiveness in specialized fields like astronomy and astrodynam…
- arXiv cs.AIagentsMemCalib: Benchmarking and Optimizing Memory Use in LLM Agents
arXiv:2609.24259v3 Announce Type: replace-cross Abstract: The effectiveness of agent memory ultimately depends on whether the underlying LLM gives each memory in context an appropriate degree of influence over its respon…
- arXiv cs.AIresearchvla.simd: Efficient CPU Inference for Language-Conditioned Manipulation
arXiv:2609.24274v1 Announce Type: cross Abstract: Deploying language-conditioned manipulation without a dedicated GPU requires efficient inference and action chunks that cover the delay between policy queries. We present…
- arXiv cs.AIresearchTemporal Generalization and Explanation Stability of Control Flow Graph Neural Networks for Malware Detection
arXiv:2609.24280v1 Announce Type: cross Abstract: Malware detection is a critical task in cybersecurity, and graph neural networks over control flow graphs have shown promising results for it. However, detectors are usua…
- arXiv cs.AIagentsTTSE: A Two-Track Online Self-Evolution Framework
arXiv:2609.24289v1 Announce Type: cross Abstract: As Large Language Model (LLM) agents are applied in continuously interactive environments, driving the evolution of their own capabilities becomes a core problem for achi…
- arXiv cs.AIresearchKV-COBRA: KV Cache Compression via Co-Optimized Bit-Rank Allocation
arXiv:2609.24298v1 Announce Type: cross Abstract: What limits KV-cache compression at extreme bit-rates? We argue that it is not the choice of compression scheme, but how its budget is allocated across attention heads. E…
- arXiv cs.AIresearchAdapting Boltz-2 with limited experimental activity data improves early enrichment in virtual screening
arXiv:2609.24302v1 Announce Type: cross Abstract: Virtual screening aims to prioritize active compounds from large chemical libraries within a limited experimental budget. When applying Boltz-2 to virtual screening, a ke…
- arXiv cs.AIresearchThe Undetected Damage of Quantization on Retrieval and How to Fix It
arXiv:2609.24322v2 Announce Type: replace-cross Abstract: We show that a quantized model that keeps its classification accuracy still changes $14$ to $46\%$ of its top-1 retrieval results, and that aggregate ranking metr…
- arXiv cs.AIagentsA Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approach
arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level task execution. Their…
- arXiv cs.AIresearchMitigating Entity Type Confusion in Cross-Domain NER via Multidimensional Quantification and Reasoning Enhancement
arXiv:2609.24357v1 Announce Type: cross Abstract: Cross-domain Named Entity Recognition (CD-NER) aims to transfer the rich knowledge in the source domain to the target domain. Recent studies adopting decomposition or gen…
- arXiv cs.AIagentsDissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection
arXiv:2609.24359v1 Announce Type: cross Abstract: Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while most forensic dete…
- arXiv cs.AIresearchDeceptionAnalyser: A Web-Based AI Tool for Performing Structured Deception Analysis with Argumentation Schemes and LLMs
arXiv:2609.24369v1 Announce Type: cross Abstract: Deception plays a central role in Intelligence operations, yet it remains difficult to analyse systematically without expert knowledge of reasoning patterns and cognitive…
- arXiv cs.AIresearchURA-NER: A Unified Retrieval-Augmented Framework with Retrieval Alignment and Uncertainty Reduction for Low-Resource NER
arXiv:2609.24372v1 Announce Type: cross Abstract: In-context learning (ICL) based on large language models (LLMs) has shown promising potential in alleviating performance bottlenecks caused by the limited availability of…
- arXiv cs.AIresearchInformation-Time Proximal Policy Optimization
arXiv:2609.24380v1 Announce Type: cross Abstract: RLVR has substantially improved the reasoning capabilities of LLMs. However, existing methods typically parameterize temporal progression in the Markov Decision Process b…
- arXiv cs.AIresearchTactile-JEPA: Topology-Aware Self-Supervised Representation Learning for Distributed Tactile Sensors
arXiv:2609.24385v1 Announce Type: cross Abstract: Tactile sensing is an essential modality for robots performing contact-rich, dexterous manipulation, particularly under visual occlusion. While pre-trained image encoders…
- arXiv cs.AIresearchArtificial Structure Function Search: Preserving Artificial Functional Connectivity for Structured Pruning
arXiv:2609.24401v1 Announce Type: cross Abstract: Structured pruning is a model compression technique that is used to reduce the computational cost of deploying deep neural networks on resource-constrained devices. Popul…
- arXiv cs.AIresearchARM: Attention with Routed-Memory for Learnable Sparse Control
arXiv:2609.24417v1 Announce Type: cross Abstract: Despite advances in long-context inference, large language models (LLMs) remain fundamentally limited by the key-value (KV) caching mechanisms that are necessary for stab…
- arXiv cs.AIresearchEstimating Accurate Hand Pose in Camera Space with Vision Transformer
arXiv:2609.24424v2 Announce Type: replace-cross Abstract: Monocular RGB-based hand pose estimation has emerged as a critical research frontier in computer vision. The local hand pose estimation methods predict hand poses…
- arXiv cs.AIresearchFoldQuantVLA: Native Low-Bit Quantization of Vision-Language-Action Models via Consistent Folding
arXiv:2609.24433v1 Announce Type: cross Abstract: Low-bit vision-language-action inference must reduce observation-to-action latency while preserving robot behavior. We present FoldQuantVLA, a post-training quantization…
- arXiv cs.AIresearchWPBench: A Comprehensive Benchmark for Wind Power Forecasting
arXiv:2609.24444v1 Announce Type: cross Abstract: Accurate, reliable, and deployable wind power forecasting is critical for power system dispatch, renewable energy integration, and electricity market operations. Progress…
- arXiv cs.AIagentsActGov: Governing LLM Agent Actions via Policy-Constrained Validation
arXiv:2609.24446v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subsequent actions a…
- arXiv cs.AIresearchDo LiDAR Language Models Really Understand Spatio-temporal Relationships?
arXiv:2609.24452v1 Announce Type: cross Abstract: Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships. Yet, in our evaluation, always selecting the same option nearly matc…
- arXiv cs.AIresearchConduit: An Experience Data Plane for Distributed Reinforcement Learning
arXiv:2609.24456v1 Announce Type: cross Abstract: Distributed reinforcement learning (RL) scales training by parallelizing actors and learners around an Experience Buffer. As RL workloads grow, however, the buffer become…
- arXiv cs.AIresearchVPRune: Efficient Training-free Pre-LLM Visual Token Pruning
arXiv:2609.24485v2 Announce Type: replace-cross Abstract: Visual token pruning is a promising approach to reducing the inference cost of large vision-language models (LVLMs), yet aggressive token reduction often causes s…
- arXiv cs.AIagentsAgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos
arXiv:2609.24487v1 Announce Type: cross Abstract: In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first estimate dense pixe…
- arXiv cs.AIresearchLifted Bellman Linear Programming for Offline Reinforcement Learning
arXiv:2609.24489v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) typically trains a critic by minimizing a regression loss against bootstrapped value targets stabilized by target networks wit…
- arXiv cs.AIresearchOn Emergent Capabilities and Model Merging
arXiv:2609.24504v2 Announce Type: replace-cross Abstract: Fine-tuned checkpoints and adapters now fill public repositories, and the most common operation applied to these artifacts is model merging: arithmetic on their w…
- arXiv cs.AIagentsBeyond Predictable Paths: Redefining AI Security Incident Reporting for Agents
arXiv:2609.24515v1 Announce Type: cross Abstract: AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting becomes increasingly impor…
- arXiv cs.AIresearchQLoRA Fine-Tuning of Ministral LLM for Sequence-to-Function Protein Annotation
arXiv:2609.24538v1 Announce Type: cross Abstract: Functional annotation of newly sequenced proteins remains a bottleneck in molecular biology: the number of sequences in public repositories grows far faster than the capa…
- arXiv cs.AIresearch$t_0$: A Time-Series Foundation Model for Forecasting with Context
arXiv:2609.24559v1 Announce Type: cross Abstract: We present $t_0$, a family of open-weights foundation models for forecasting with multivariate context. We release its first two members: $\texttt{t0-alpha}$ and $\texttt…
- arXiv cs.AIresearchOverlay\_dx - Automating forecasting evaluation
arXiv:2609.24586v1 Announce Type: cross Abstract: Traditional evaluation metrics provides numerical values but often lack comprehensibility, hindering effective differentiation of model performances. Our work addresses t…