AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchQuPID: Quantum Parameter-Efficient Input-Dependent Retrieval Adaptation for Medical RAG
arXiv:2609.33351v1 Announce Type: new Abstract: Fidelity-based quantum retrieval ranks candidates by the fidelity between query and archive states. Applying a shared input-independent unitary after fixed state encoding l…
- arXiv cs.AIresearchUnmask the State: When Does State Adaptation Matter for Masked Diffusion Language Models
arXiv:2609.33355v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) admit flexible generation orders, making the unmasking strategy an inference decision. Existing methods vary in how they prioritize…
- arXiv cs.AIagentsLong-Horizon Analog Design Bench: Benchmarking Agents on Hours-Long Analog and Mixed-Signal Circuit Design Tasks
arXiv:2609.33356v1 Announce Type: new Abstract: Coding agents now sustain hours-long, tool-driven loops, yet their ability to carry long-horizon analog and mixed-signal circuits to electrical specification remains unmeas…
- arXiv cs.AIagentsDISCERN: Can AI Agents Work Like Scientists and Guide Discovery?
arXiv:2609.33357v2 Announce Type: replace Abstract: Reliable automated research requires agents to vet data, verify analyses, and generate hypotheses grounded in trustworthy evidence, potentially reducing routine scienti…
- arXiv cs.AIresearchDrafTS: Time-Aware Decomposition with Residual Correction for Time Series Modeling
arXiv:2609.33368v1 Announce Type: new Abstract: Real-world time series contain evolving underlying dynamics with irregular variations that lack stable temporal patterns and are often referred to as noise. Existing method…
- arXiv cs.AIresearchCross-modal Translation via Conditional Latent Denoising for Video Deepfake Detection
arXiv:2609.33394v1 Announce Type: new Abstract: The growing threat of video deepfakes necessitates multimodal detection. Beyond serving as independent indicators of authenticity, audio and visual signals have intrinsic d…
- arXiv cs.AIresearchCoViST: Visual Token Compression via Composable States
arXiv:2609.33397v1 Announce Type: new Abstract: Visual token compression lowers the inference cost of vision--language models by representing images with fewer tokens. However, most existing methods compress visual token…
- arXiv cs.AIresearchCOEVO: Co-Evolving Context and Parameters for Recursive Self-Improvement
arXiv:2609.33398v1 Announce Type: new Abstract: Recursive self-improvement (RSI) seeks to move large language models beyond static training pipelines toward systems that can participate in improving their own future beha…
- arXiv cs.AIresearchMetaBench-Harness: Unlocking End-to-End Optimization of Benchmark Harnesses
arXiv:2609.33411v1 Announce Type: new Abstract: Rapid progress in Large Language Models (LLMs) is saturating static benchmarks faster than they can be designed. While existing automated evolution frameworks attempt to ge…
- arXiv cs.AIresearchTemporal Graph Learning of Wearable Actigraphy and Sleep Traces for Modelling Adolescent Crystallized Intelligence
arXiv:2609.33428v1 Announce Type: new Abstract: Wearable actigraphy offers a scalable, ecologically valid alternative to episodic clinical assessment. However, predicting continuous adolescent crystallized intelligence (…
- arXiv cs.AIagentsAPEX: An Extensible Model for Agent-Assisted Production Scheduling
arXiv:2609.33430v1 Announce Type: new Abstract: Production scheduling requires realistic models that reflect operational constraints and efficient methods that balance competing goals. Putting these methods into use also…
- arXiv cs.AIagentsRaven: The Harness of Harnesses for Composable Agentic Intelligence
arXiv:2609.33439v1 Announce Type: new Abstract: As large language models advance, AI agents are moving beyond isolated, domain-specific tasks toward long-horizon, cross-domain workflows. This transition exposes two chall…
- arXiv cs.AIresearchMAC-Net: A Multi-Task Deep Learning Framework for Modeling Cognitive Function From Task-Based fMRI
arXiv:2609.33440v1 Announce Type: new Abstract: Objective cognitive assessment from neural signals supports neurorehabilitation, but individual-level prediction from task-based fMRI (tfMRI) remains difficult because neur…
- arXiv cs.AIresearchWhat Shared Prefixes Hide: Trajectory Dropout for On-Policy Distillation
arXiv:2609.33455v2 Announce Type: replace Abstract: On-policy distillation (OPD) trains a student model on its own trajectories using dense token-level feedback from a stronger teacher model. Since each update is conditi…
- arXiv cs.AIresearchWhen Does the Concept of "Dog" Emerge in an Audio LLM?
arXiv:2609.33458v1 Announce Type: new Abstract: Multimodal large language models answer audio questions, but how they represent auditory semantics and use them in decisions remains unclear, limiting our understanding of…
- arXiv cs.AIagentsLiveOption: Evaluating LLM Agents in Structured Option Trading with Nonlinear Payoffs
arXiv:2609.33470v2 Announce Type: replace Abstract: Large language models (LLMs) and multi-agent systems (MAS) have shown promise in financial decision-making, yet existing evaluations focus on equity trading and primari…
- arXiv cs.AIresearchJust Let Linear States Forget the Distant Past: Prefix Caching via Suffix Replay for Hybrid LLMs
arXiv:2609.33477v1 Announce Type: new Abstract: Hybrid LLMs interleave full-attention layers with linear-attention layers to reduce long-context inference cost, but this structure complicates prefix caching. Full-attenti…
- arXiv cs.AIagentsFedMHAR: Federated Multimodal Human Activity Recognition using Multi-Agent Reinforcement Learning
arXiv:2609.33492v2 Announce Type: replace Abstract: Human Activity Recognition (HAR) from heterogeneous wearable sensors is fundamental to the Internet of Health Things (IoHT), supporting rehabilitation, elderly care, an…
- arXiv cs.AIresearchRelaxKV: Recomputation Guided by the Query with Sparse Context Attention for Efficient KV Cache Reuse
arXiv:2609.33503v1 Announce Type: new Abstract: Cross-request KV caching reduces the prefill cost of Retrieval-Augmented Generation (RAG), but conventional prefix caching severely limits cache reuse across requests. Posi…
- arXiv cs.AIresearchWhen Evidence Changes the Subject: Subject-Typed Claim Licensing for Learned Routing
arXiv:2609.33505v1 Announce Type: new Abstract: Modern learned systems increasingly combine learned components with search, repair, or external solvers. Benchmarks often measure the resulting end-to-end system, while sci…
- arXiv cs.AIagentsWhat Happens During Autonomous Deep Research After the User Steps Away?
arXiv:2609.33509v1 Announce Type: new Abstract: In autonomous deep research, a user provides a task and relevant background, then leaves the agent to conduct an extended investigation without further human intervention.…
- arXiv cs.AIresearchPPG-LM: A Photoplethysmography-Language Model with Multi-Level Clinical Alignment
arXiv:2609.33516v1 Announce Type: new Abstract: Photoplethysmography (PPG) is widely recorded by clinical monitors and consumer wearables, providing a scalable source of continuous physiological information. These record…
- arXiv cs.AIagentsEverMine: Dissecting the Self-Evolution of Research Capabilities in Long-Horizon Alpha Research
arXiv:2609.33524v1 Announce Type: new Abstract: Self-evolving agents aim to turn research feedback into reusable skills, tools, and research rules. Whether these accumulated capabilities continue to improve later researc…
- arXiv cs.AIresearchReasoning on the Simplex: Geometric Fixed-Point Models
arXiv:2609.33540v1 Announce Type: new Abstract: Looped reasoners spend test-time compute by iterating a weight-tied map, but a small residual does not mean the state is a fixed point when that map lives in unconstrained…
- arXiv cs.AIresearchOSCC: Certified Observation-Safe Coupling Optimization for Gradient-Noise Control in Imperfect-Information Learning
arXiv:2609.33543v2 Announce Type: replace Abstract: Coupled rollouts can reduce the noise of counterfactual action comparisons, but two issues prevent standard common-random-number constructions from serving as a general…
- arXiv cs.AIagentsDr. Free: You Don't Need Difficulty Rewards for Self-Evolving Search Agents
arXiv:2609.33565v1 Announce Type: new Abstract: A central limitation of current data-free self-evolution methods for training search agents is their reliance on difficulty-based proposer rewards. These methods reward a p…
- arXiv cs.AIresearchOpenFC: Learning Verification Policies towards Open-Search Fact Checking
arXiv:2609.33579v1 Announce Type: new Abstract: Open-search fact checking is not merely retrieval followed by classification, but a sequential decision problem in which every query, source visit, and stopping decision re…
- arXiv cs.AIresearchJustQuant: You Don't Need Smoothing, SVD, or Rotation for 4-Bit Activation Quantization
arXiv:2609.33601v1 Announce Type: new Abstract: Recent generative models have become increasingly powerful, but their inference cost continues to grow. Model quantization offers a promising way to compress these models a…
- arXiv cs.AIresearchSupervision Recovery for Time Series Anomaly Detection via Context-Anchored Pairing
arXiv:2609.33610v1 Announce Type: new Abstract: Time series anomaly detection (TSAD) remains challenging not only because anomaly labels are scarce, but also because temporal anomalies are highly context-dependent. Exist…
- arXiv cs.AIresearchEAT: Expert Account Tracker for Efficient MoE Inference
arXiv:2609.33614v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have emerged as a revolutionary method to scale Transformer models. However, traditional MoE architecture still suffers from inefficiency si…
- arXiv cs.AIagentsParaAgent: Reinforcing Parallel Acting in Open-World Tool Environments
arXiv:2609.33618v1 Announce Type: new Abstract: Language model agents are increasingly deployed in open-world tool environments, which require balancing exploring unknown capabilities and exploiting known ones. Existing…
- arXiv cs.AIagentsTrajectory Unlearning on LLM-based Agents
arXiv:2609.33639v1 Announce Type: new Abstract: Existing large language model (LLM) unlearning has focused primarily on removing specific knowledge, such as harmful facts, private data, or copyrighted content. However, a…
- arXiv cs.AIresearchScalable and Data-Driven Decision Support in the Maintenance, Repair, and Overhaul Process
arXiv:2609.33641v1 Announce Type: new Abstract: Several businesses apply maintenance, repair, and overhaul (MRO) principles to the life-cycle of their existing products. In cases like casted gas turbine component Product…
- arXiv cs.AIagentsProbe to Act: Elevating Browser-Use Agent via Active Visual Probing
arXiv:2609.33646v1 Announce Type: new Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long interactions. Existing i…
- arXiv cs.AIagentsAgentBoundary: Counterfactual Evaluation of Safety in Tool-Using LLM Agents
arXiv:2609.33658v1 Announce Type: new Abstract: Safety alignment for large language models (LLMs) in conversational settings is largely framed around whether to answer or refuse a request. In agentic settings, however, t…
- arXiv cs.AIresearchAudit-First VAPO: Risk-Certified Selective Updates under Imperfect Verification
arXiv:2609.33662v2 Announce Type: replace Abstract: Imperfect verifiers can assign a harmful update direction even when clipping and regularization bound its magnitude. We introduce Audit-First VAPO, which separates disc…
- arXiv cs.AIagentsCompoWorld: Compositional Environment Scaling for General Agents
arXiv:2609.33665v2 Announce Type: replace Abstract: Automatically generated environments provide a scalable source of interaction data for training general agents. However, existing approaches mainly generate tasks withi…
- arXiv cs.AIresearchRSD-Poker: Structure-Adaptive and Shift-Robust Risk-Utility Certification for Residual Policies in Imperfect-Information Games
arXiv:2609.33669v2 Announce Type: replace Abstract: Residual policy adaptation provides a lightweight way to modify a strong reference policy, but a shared scale and a fixed subgroup partition can hide heterogeneous degr…
- arXiv cs.AIagentsAuditing Agent Actions through Query-Conditioned Attribution
arXiv:2609.33676v2 Announce Type: replace Abstract: LLM agents increasingly take consequential actions through interactions with users, policies, and external tools. Auditing these agents requires automated attribution o…
- arXiv cs.AIagentsSWE-Game: Can Coding Agents Build the Games We Want?
arXiv:2609.33678v3 Announce Type: replace Abstract: We introduce SWE-Game, a benchmark of 247 tasks grounded in 41 executable reference Godot games spanning 13 gameplay categories in 2D and 3D. Five task types cover deve…
- arXiv cs.AIresearchTopoMamba: A Load-Support Relation-Guided Multi-Directional State-Space Model for Topology Optimization
arXiv:2609.33688v1 Announce Type: new Abstract: Deep learning has emerged as an efficient alternative for predicting high-performance material distributions in topology optimization. Existing methods struggle to accurate…
- arXiv cs.AIresearchOne Latent, Many Tokens: Jointly Learning Compressed Embeddings for Efficient Language Diffusion
arXiv:2609.33698v1 Announce Type: new Abstract: Most continuous diffusion language models process one latent position per token at each sampling step, making generation expensive. Two-stage methods lower the cost by redu…
- arXiv cs.AIresearchSpecRead: A Benchmark for Measuring Whether Language Models Understand Hardware Specifications
arXiv:2609.33699v1 Announce Type: new Abstract: Existing benchmarks for large language models (LLMs) in hardware design evaluate downstream artifacts such as generated RTL, assertions, or testbenches. When a model fails…
- arXiv cs.AIresearchDoes Adversarial Training Improve Generalization in Multi-View VLAs? Revealing and Mitigating View Collapse
arXiv:2609.33707v1 Announce Type: new Abstract: Vision-language-action (VLA) models adapt pretrained vision-language models (VLMs) for closed-loop robot control, transferring their perceptual and semantic capabilities to…
- arXiv cs.AIresearchBIRD: Distilling Decision Boundaries into Rationales for MLLM Adaptation
arXiv:2609.33713v1 Announce Type: new Abstract: Adapting general-purpose multimodal large language models (MLLMs) to specialized domains requires learning domain-specific decision criteria, which often hinge on subtle vi…
- arXiv cs.AIagentsSelf-Designed Evaluators and Warm Memory for Long-Horizon Agents
arXiv:2609.33717v1 Announce Type: new Abstract: A tool-using language-model agent deployed over a long stream of tasks receives no reward, so it cannot tell whether it succeeded, cannot safely retry, and cannot label the…
- arXiv cs.AIresearchRobust Biomolecular Complex Design Across Protein Conformational Landscapes
arXiv:2609.33726v2 Announce Type: replace Abstract: Proteins populate conformational ensembles, yet structure-based biomolecular design typically optimizes candidates against a single target conformation. Consequently, a…
- arXiv cs.AIagentsHTN Planning as a Coordination Layer for Multi-Server MCP Tool Orchestration
arXiv:2609.33731v1 Announce Type: new Abstract: The Model Context Protocol (MCP) isolates servers by design: only the host can orchestrate cross-server workflows. When the host is a large language model, the resulting or…
- arXiv cs.AIagentsSkill2Env: Capability-Oriented Environment Synthesis from Skills for General Agents
arXiv:2609.33772v2 Announce Type: replace Abstract: Executable environments are critical for post-training agents on tasks that require tool use and multi-step interaction, but constructing executable tasks together with…
- arXiv cs.AIagentsLearning Strategies to Break Judges
arXiv:2609.33773v1 Announce Type: new Abstract: As AI agents surpass human performance, it becomes exceedingly hard for system designers to evaluate them directly and understand their failure modes. Consequently, agents…