AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchTowards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions
arXiv:2609.36502v1 Announce Type: cross Abstract: Past research using log data has faced the "learning system wall," whereby few methods exist for generalizing models of student learning across platforms. Increasingly, o…
- arXiv cs.AIresearchLarge-scale factor analysis shows machine intelligence is only partially interpretable
arXiv:2609.36515v1 Announce Type: cross Abstract: A common assumption in language model development is that cognitive abilities are organized around a general, domain-free intelligence factor, like fluid intelligence in…
- arXiv cs.AIresearchLIBERO-MAX: Do Robot Policies Adapt When the World Changes?
arXiv:2609.36518v1 Announce Type: cross Abstract: Robots must often continue a task after a target moves, the viewpoint shifts, or an obstacle appears, even though their earlier observations and committed actions reflect…
- arXiv cs.AIresearchReliability Testing of Medical Model Performance under Distributed Deployment
arXiv:2609.36525v1 Announce Type: cross Abstract: Distributed inference has become an indispensable part of deploying medical models under practical latency, memory, and throughput constraints. Although modern frameworks…
- arXiv cs.AIagentsAdapting Context Compression for Long-Horizon Agents with Counterfactual Continuations
arXiv:2609.36526v1 Announce Type: cross Abstract: Long-horizon agents require context compression to manage growing interaction histories. Compression quality, however, is ultimately determined by downstream execution. E…
- arXiv cs.AIresearchDraftTrace: A Multi-View Analytics Environment for AI-Integrated Writing
arXiv:2609.36544v1 Announce Type: cross Abstract: Generative AI has changed how students produce writing assignments. The final artifact is no longer sufficient to understand the process through which it was produced. We…
- arXiv cs.AIresearchInteractive-Policy Distillation with Bidirectional Propose-and-Verify
arXiv:2609.36546v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student model on its self-generated trajectories with dense token-level teacher feedback. However, naive OPD may suffer from teacher…
- arXiv cs.AIresearchSERA: Scale-Equalized Rollout Allocation for Maximum Likelihood Reinforcement Learning
arXiv:2609.36552v1 Announce Type: cross Abstract: Maximum Likelihood Reinforcement Learning (MaxRL) targets prompt-wise log-success and has shown strong performance on reasoning tasks. Under finite rollout budgets, howev…
- arXiv cs.AIresearchHow Medical VLMs Underutilize Their Vision Encoders: A Dermatology Perspective
arXiv:2609.36557v1 Announce Type: cross Abstract: Medical Vision-Language Models (VLMs) show significant promise for clinical image understanding, offering accurate diagnosis with interpretable reasoning. However, a crit…
- arXiv cs.AIresearchHiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation
arXiv:2609.36559v1 Announce Type: cross Abstract: Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early prefix of the timeli…
- arXiv cs.AIresearchFM-ReID: Selective Competitive Token Routing for Object Re-Identification
arXiv:2609.36560v1 Announce Type: cross Abstract: Object re-identification (ReID) faces a recurring challenge: different identities can share highly similar global appearances, while the cues that distinguish them are lo…
- arXiv cs.AIresearchThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models
arXiv:2609.36562v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, their reliability is threatened by multimodal implicit risks. Unlike…
- arXiv cs.AIresearchFrom Checkpoint Variation to Selection Gains in Supervised Fine-Tuning
arXiv:2609.36569v1 Announce Type: cross Abstract: Checkpoint selection is a routine decision in supervised fine-tuning (SFT): training produces multiple checkpoints, but only one is retained. Yet fixed-budget comparisons…
- arXiv cs.AIagentsCounterSteer: Suppressing Indirect Prompt Injection with Activation Steering
arXiv:2609.36570v1 Announce Type: cross Abstract: Indirect prompt injection makes an LLM agent treat untrusted retrieved text as instructions. We present CounterSteer, an inference-time defense that suppresses this behav…
- arXiv cs.AIresearchLong-Term Memory-Guided Enhancement for Target Perception in Audio-Language Models
arXiv:2609.36577v1 Announce Type: cross Abstract: Audio large language models (ALLMs) can reason about the content of audio recordings to perform complex tasks. However, these capabilities usually collapse in real-world…
- arXiv cs.AIresearchFactorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
arXiv:2609.36578v1 Announce Type: cross Abstract: Scheduling problems arise from repeatedly selecting one item from a set of candidates based on their states. These problems often reduce to assigning priority scores and…
- arXiv cs.AIagentsCooperative Multi-Agent Vision-Language-Action Models via Reinforced Fine Tuning
arXiv:2609.36588v1 Announce Type: cross Abstract: We study reinforcement learning (RL) methods for cooperative multi-agent Vision-Language-Action (VLA) models. This problem is challenging because VLAs are pretrained on l…
- arXiv cs.AIagentsText2Sim: Agentic Physics-Based Simulation Generation with Distilled Expertise
arXiv:2609.36593v2 Announce Type: replace-cross Abstract: Creating diverse physical simulations remains labor-intensive because assets, layout, physical parameters, motion, control, and rendering must be designed and deb…
- arXiv cs.AIagentsSimple Agentic Memory for Generalist Robot Policies
arXiv:2609.36595v1 Announce Type: cross Abstract: Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual frame may explicitly…
- arXiv cs.AIresearchScaling Video Generation for Reasoning: At What Cost?
arXiv:2609.36599v1 Announce Type: cross Abstract: We study whether scaling video generation enables models to reason about hidden information from the past frames, and at what computational cost. Our controlled benchmark…
- arXiv cs.AIresearchSecond-Moment Stochastic Approximation Methods
arXiv:2609.36600v1 Announce Type: cross Abstract: Classical stochastic approximation methods rely on estimators of the first moment (mean) of a random regression function. We study methods that employ estimators of both…
- arXiv cs.AIagentsWitnessGym: Benchmarking Coding Agents on the Construction of Bug Witnesses
arXiv:2609.36635v1 Announce Type: cross Abstract: Bug validation asks a coding agent to produce an executable witness for a reported bug. The witness combines a concrete input with a testing harness and exposes faulty be…
- arXiv cs.AIresearchInducing Process Supervision from Outcome-Only Reinforcement Learning
arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. However, training str…
- arXiv cs.AIresearchWhere Predictive Supervision Goes Shapes What VLA Policies Learn
arXiv:2609.36645v2 Announce Type: replace-cross Abstract: Future prediction is increasingly used to improve vision-language-action (VLA) policies, based on the premise that anticipating scene evolution encourages represe…
- arXiv cs.AIresearchFocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution
arXiv:2609.36651v1 Announce Type: cross Abstract: Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by rendering text as i…
- arXiv cs.AIresearchConstitutional adapters: Inference-time interventions for misalignment and misuse
arXiv:2609.36657v1 Announce Type: cross Abstract: Training models to act in accordance with an explicitly defined set of principles, or "constitution," has shown promise as a robust and transparent mechanism for AI align…
- arXiv cs.AIresearchAutoLoCo: Communication Efficient Distributed LLM Training via Adaptive Synchronization
arXiv:2609.36662v1 Announce Type: cross Abstract: The pre-training of Large Language Models (LLMs) is increasingly conducted across multiple data centers. As training scales to a larger number of accelerators, the fracti…
- arXiv cs.AIresearchMyoCodec: A Streaming Neural Codec for Electromyography
arXiv:2609.36687v1 Announce Type: cross Abstract: Neural codecs encode continuous signals into compact sequences of discrete tokens, providing an interface for efficient transmission, storage, and token-based sequence mo…
- arXiv cs.AIresearchNormalize-Then-Precondition: A Hierarchical Approach to Marginal Scale and Interaction Geometry for LLM Training
arXiv:2609.36692v1 Announce Type: cross Abstract: Matrix optimizers have emerged as a promising direction, with Muon standing out as a prominent design. Revisiting Muon through its full-Gram representation, we observe th…
- arXiv cs.AIresearchLost in Conversation or Lost in Translation? Diagnosing Multi-Turn Degradation in RAG
arXiv:2609.36700v1 Announce Type: cross Abstract: When conversing with large language models (LLMs), users often begin with a simple question and build towards a multi-hop question through follow-up turns. Retrieval-augm…
- arXiv cs.AIagentsFrontier Autolab: Organizational Memory, Adversarial Dissent and Temporal Leakage in Multi-Agent LLM Firms Across Fifty Years of Technological Change
arXiv:2609.36739v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly structured like organizations, with roles, critics and shared memory, yet they are evaluated on tasks that last minutes. We ask h…
- arXiv cs.AIresearchGroup-Marginalized Self-Rewarding RL Drives Zero-Label Self-Evolving
arXiv:2609.36750v1 Announce Type: cross Abstract: Self-rewarding reinforcement learning (RL) enables large language models (LLMs) to self-evolve without human labels. Existing ensemble-based methods construct reward refe…
- arXiv cs.AIresearchNesTok: Nested Self-Aligned 1D Tokenizer for Autoregressive Image Generation
arXiv:2609.36756v3 Announce Type: replace-cross Abstract: One-dimensional (1D) variable-length visual tokenizers enable adaptive compression by varying the number of tokens, allowing downstream autoregressive (AR) models…
- arXiv cs.AIresearchDual-Mode Low-Rank Learner with Bridge-Prototype Ensemble for Vision-Language Class-Incremental Learning
arXiv:2609.36759v1 Announce Type: cross Abstract: Benefiting from transferable visual-textual alignment, CLIP has been widely adopted for class-incremental learning (CIL). However, existing learners either repeatedly upd…
- arXiv cs.AIresearchBeyond Conditional Independence: Root Cause Analysis with Deep Causal Models
arXiv:2609.36771v1 Announce Type: cross Abstract: Root cause analysis (RCA) is a critical problem in many real-world scenarios. RCA enables the identification of faulty or failing mechanisms in a system by comparing anom…
- arXiv cs.AIresearchVAA-CSEC: Vote-guided Advantage Allocation for Chinese Semantic Error Correction
arXiv:2609.36804v1 Announce Type: cross Abstract: Chinese Semantic Error Correction (CSEC) targets semantic errors in Chinese text, which are typically more subtle and complex than spelling and grammatical errors but rem…
- arXiv cs.AIresearchSpotter: Let the Embodied Model Lead, and the VLM Reflect for It
arXiv:2609.36808v1 Announce Type: cross Abstract: Current embodied models do not respond to their own failures, although what just went wrong could inform a small adjustment on the next attempt, the kind of reflection be…
- arXiv cs.AIresearchDiffusion Policy Improvement with Proposal-Conditioned Refinement Flows
arXiv:2609.36812v2 Announce Type: replace-cross Abstract: Diffusion and flow policies can model complex behaviors in offline reinforcement learning (RL). However, penalizing their KL divergence from the behavior policy c…
- arXiv cs.AIagentsOn-Policy Visual Evidence Distillation
arXiv:2609.36838v1 Announce Type: cross Abstract: Visual agents solve problems by interleaving reasoning with image operations, and on-policy distillation (OPD) provides guidance from a strong teacher on student-generate…
- arXiv cs.AIresearchDSWM: Decomposed Spatio-Temporal World Model for Demand-Driven UAV Base Station Repositioning
arXiv:2609.36845v1 Announce Type: cross Abstract: Uncrewed aerial vehicle base stations (UAV-BSs) are expected to cover traffic demand that shifts across space and time, yet most repositioning schemes either re-solve an…
- arXiv cs.AIagentsDoes the Unsafe Gradient Survive a Conversation? On the Fragility of Gradient-Based Jailbreak Detection in Multi-Turn Dialogue
arXiv:2609.36849v1 Announce Type: cross Abstract: Safety-aligned language models are commonly deployed as multi-turn assistants, which lets adversaries spread unsafe intent across several user turns instead of a single p…
- arXiv cs.AIresearchSafer Content or Firmer Refusals? A Hybrid Perturbation Defense for Alignment under Harmful Fine-tuning
arXiv:2609.36862v1 Announce Type: cross Abstract: Fine-tuning-as-a-service lets users adapt a safety-aligned language model to their own data, but it also creates a harmful fine-tuning attack surface: a small amount of h…
- arXiv cs.AIagentsSKILLLITE: Evidence-Guided Malicious Skill Auditing with Compact LLMs
arXiv:2609.36879v1 Announce Type: cross Abstract: As LLM-based agents perform increasingly complex tasks, Agent Skills have emerged as a flexible mechanism for extending their capabilities. An Agent Skill packages task-s…
- arXiv cs.AIresearchDigital Twin Modeling of Quantum Dynamical Systems: Dissipative Quantum Reservoir Computing
arXiv:2609.36901v1 Announce Type: cross Abstract: Modeling the response of driven many-body quantum systems from input--output data is difficult: the dynamics are nonlinear, history dependent, and expensive to simulate a…
- arXiv cs.AIresearchMultiTalk: Scaling Full-Duplex Speech Models to Long, Multi-Party, Bilingual Conversation
arXiv:2609.36903v1 Announce Type: cross Abstract: End-to-end full-duplex speech models have brought open-source machine conversation closer to human-like interaction, yet existing systems remain limited in two intertwine…
- arXiv cs.AIresearchBaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR
arXiv:2609.36913v1 Announce Type: cross Abstract: Transcribing domain-specific entities and rare proper nouns remains a major challenge in automatic speech recognition (ASR). In this paper, we propose BaLEEN (Biasing wit…
- arXiv cs.AIresearchAeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations
arXiv:2609.36915v1 Announce Type: cross Abstract: Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities for general-purpose ma…
- arXiv cs.AIresearchState Transport Routing for Short-horizon Adaptation in Multi-horizon Photovoltaic Forecasting
arXiv:2609.36926v1 Announce Type: cross Abstract: Recent power measurements provide valuable information for photovoltaic(PV) power forecasting, but directly extrapolating short-term trends can introduce substantial erro…
- arXiv cs.AIresearchWeLike2Party! In-Context Motion Transfer for Multi-Human Image Animation
arXiv:2609.36937v3 Announce Type: replace-cross Abstract: Human image animation aims to transfer motion from a driving video to subjects in a reference image. Despite remarkable progress in video generation, achieving hi…
- arXiv cs.AIresearchSafe-by-Design Learning via Energy-based Neural Networks
arXiv:2609.36942v2 Announce Type: replace-cross Abstract: Learning neural-network models of dynamical systems with safety guarantees is a fundamental requirement for their deployment in safety-critical settings. Safety i…