AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchLearning Continuous Neural Representation of Stochastic Hybrid Systems
arXiv:2609.38893v1 Announce Type: cross Abstract: A stochastic hybrid system (SHS) is governed by a stochastic differential equation (SDE) describing the continuous dynamics and a Markov reset kernel triggered on the gua…
- arXiv cs.AIresearchUnmerge: Efficient Machine Unlearning via Task Arithmetic
arXiv:2609.38895v1 Announce Type: cross Abstract: Approximate machine unlearning seeks to remove the influence of a forget set from a trained model without full retraining. Existing gradient-based methods require data-de…
- arXiv cs.AIresearchFFASR: Benchmarking Far-Field Automatic Speech Recognition using High-Fidelity Simulated RIRs
arXiv:2609.38897v1 Announce Type: cross Abstract: Far-field automatic speech recognition(ASR) degrades under reverberation, noise, and talker motion, yet the benchmarks that drive model selection emphasize close-micropho…
- arXiv cs.AIresearchSceneJail: Exploiting Video Scenario Context to Jailbreak Multimodal LLMs
arXiv:2609.38899v1 Announce Type: cross Abstract: Video Multimodal Large Language Models (Video-MLLMs) support reasoning over video inputs, yet remain vulnerable to jailbreak attacks that elicit policy-violating response…
- arXiv cs.AIresearchDAMPER: Return-Prioritized Gradient Control for Smooth Policies
arXiv:2609.38903v1 Announce Type: cross Abstract: Actor-critic methods achieve strong performance in continuous control, but their policies can produce highly oscillatory actions. A common remedy is to add auxiliary smoo…
- arXiv cs.AIresearchCharacterizing Questioning Patterns and Student Engagement Through Contextual Analysis of Real-Time Classroom Interactions
arXiv:2609.38907v1 Announce Type: cross Abstract: Real-time classroom polling is now routine, yet the data it produces is usually read narrowly, as a correctness score or a headcount. Such readings say little about what…
- arXiv cs.AIresearchCellMSA: Context Modeling for Single-Cell Representation Learning
arXiv:2609.38908v1 Announce Type: cross Abstract: Single-cell transcriptomics enables profiling of cellular states at unprecedented resolution, but its high dimensionality, sparsity, and technical batch effects pose sign…
- arXiv cs.AIresearchUnlearning Deceptive Behaviors in LLMs with Contrastive Forget Sets
arXiv:2609.38909v1 Announce Type: cross Abstract: Large language models often know the truth and say otherwise: a model that answers correctly when asked neutrally will affirm a user's mistaken belief, or misstate a fact…
- arXiv cs.AIresearchOn the Relaxation of Conditional Independence Assumption for Image Segmentation
arXiv:2609.38930v2 Announce Type: replace-cross Abstract: In semantic segmentation, a recent line of RankSEG methods directly optimizes Dice/IoU scores at inference time, improving alignment with evaluation metrics witho…
- arXiv cs.AIresearchAdaptive Self-Consistency: From Black-Box Sampling to Distribution-Valued Feedback
arXiv:2609.38931v1 Announce Type: cross Abstract: Self-consistency samples many reasoning trajectories and aggregates their final answers, treating the LLM as a black box that returns one answer per trajectory. Yet the f…
- arXiv cs.AIresearchSignal-Routed Temperature Scaling: Low-Capacity Risk-Conditioned Calibration for Small Validation Budgets
arXiv:2609.38936v1 Announce Type: cross Abstract: When a classifier is recalibrated from only a few thousand held-out examples, the capacity of the calibration map becomes a statistical design choice rather than a purely…
- arXiv cs.AIresearchDrivingBench: Can Vision-Language Models Drive a Toyota Corolla?
arXiv:2609.38948v1 Announce Type: cross Abstract: Frontier models excel at many digital benchmarks, yet their ability to drive a real car, an everyday human skill, remains largely untested. We present DrivingBench, to ou…
- arXiv cs.AIagentsAPTInvestBench: Evaluating Autonomous APT Investigation under Varying Telemetry
arXiv:2609.38954v1 Announce Type: cross Abstract: Large language model (LLM) agents could help security operations centers (SOCs) investigate advanced persistent threats (APTs) by turning weak leads into evidence for int…
- arXiv cs.AIresearchLoop-Free Inverse Reinforcement Learning via Sequential Value Recovery with Q-Score Matching
arXiv:2609.38955v1 Announce Type: cross Abstract: Inverse Reinforcement Learning (IRL) aims to recover a reward function that explains expert demonstrations. Existing IRL methods typically rely on a bi-level optimization…
- arXiv cs.AIresearchMaking LLMs Say What They Think: Measuring and Improving CoT-Interpretability Alignment
arXiv:2609.38972v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) traces often serve as a proxy for how Large Language Models (LLMs) arrive at their answers. However, growing evidence shows that models' Co…
- arXiv cs.AIresearchScale-Split Neural Operator for Memory- and Data-Efficient 3D Turbulence Prediction
arXiv:2609.38977v1 Announce Type: cross Abstract: Neural surrogates have emerged as fast alternatives to the numerical simulation of three-dimensional turbulence. However, training them at high resolution remains challen…
- arXiv cs.AIagentsSimEX: Simulation-Integrated Robotics AutoResearch
arXiv:2609.38982v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital world. However, bringi…
- arXiv cs.AIagentsApproval Laundering: Systematizing Approval--Execution Binding Failures in AI Coding-Agent Harnesses
arXiv:2609.38983v1 Announce Type: cross Abstract: Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a human approves is t…
- arXiv cs.AIresearchSparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination
arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and actions. This capabi…
- arXiv cs.AIresearchThe Invisible Language Tax: Token Premiums of French and Regional Languages in 2026 LLM Tokenizers, and a French-Optimized Prototype
arXiv:2609.39001v1 Announce Type: cross Abstract: LLM services are billed per token and context windows are measured in tokens, yet the number of tokens needed for the same content varies across languages. We measure thi…
- arXiv cs.AIresearchAn Uncertainty-Guided Digital Twin Framework for Online Adaptive Proton Therapy in Head and Neck Cancer: A Feasibility Study
arXiv:2609.39010v1 Announce Type: cross Abstract: Objective: Head and neck (HN) proton therapy spans six to seven weeks of anatomical change, while offline replanning takes about a week. We present an uncertainty-guided…
- arXiv cs.AIagentsMake Code as Policy Great Again: Frontier Agents Write, Call, and Evolve Robot Tools
arXiv:2609.39018v1 Announce Type: cross Abstract: Frontier models can control robots, but reasoning through every reach, grasp, and retreat makes manipulation slow and token-intensive. We revisit code as policy with a di…
- arXiv cs.AIagentsFrom Verification Failures to Reusable Guidance for Coding Agents
arXiv:2609.39022v3 Announce Type: replace-cross Abstract: Coding agents need to establish that a program satisfies a specification and that the specification captures the requested behavior. We study how expert diagnosis…
- arXiv cs.AIresearchTED:Text-Axis Evidence Decomposition for Prompted Anomaly Localization
arXiv:2609.39033v1 Announce Type: cross Abstract: CLIP is a powerful vision-language model, but it was not designed for fine-grained defect localization; CLIP-based anomaly detectors therefore adapt it with prompts or li…
- arXiv cs.AIresearchSwitching Linear Attention
arXiv:2609.39034v1 Announce Type: cross Abstract: Designing expressive sequence layers with efficient inference remains a central challenge in modern machine learning. Standard softmax attention achieves excellent sequen…
- arXiv cs.AIresearchCycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection
arXiv:2609.39035v1 Announce Type: cross Abstract: Passenger access doors are safety-critical subsystems in railway vehicles, yet detecting abnormal door behavior in real operation is challenging because faults are rare,…
- arXiv cs.AIresearchHard-Gate Candidacy in a Deployed Validator Suite
arXiv:2609.39037v1 Announce Type: cross Abstract: Before a validator can be promoted to a hard gate on a deployment pipeline, it has to be shown that its firing separates outputs that reach users in working order from th…
- arXiv cs.AIresearchStructure-aware Reinforcement Learning for Protein Directed Evolution
arXiv:2609.39048v1 Announce Type: cross Abstract: Protein optimization remains a longstanding goal in life sciences. Existing machine learning-assisted directed evolution (MLDE) methods primarily rely on sequence-only fe…
- arXiv cs.AIresearchStructure vs. Chain-of-Thought: Evaluating LLM Criteria Extraction for Depression Severity
arXiv:2609.39049v2 Announce Type: replace-cross Abstract: A large language model (LLM) can rate depression severity directly from a social media post, or mark which clinical criteria the post shows and let a simple rule…
- arXiv cs.AIresearchA 3GPP-Compliant Benchmark Dataset for RIS-Aided Beyond 5G Networks
arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (B5G) networks. Howev…
- arXiv cs.AIagentsCan Agents Trust Their Skills? Uncovering Unsafe Chains of Trust in Skill-Based LLM Agents
arXiv:2609.39065v1 Announce Type: cross Abstract: LLM agents increasingly rely on installable skills, which are packages of instructions, code, and resources that equip them with task-specific capabilities and, once inst…
- arXiv cs.AIresearchBeyond Text: LLM-Based Dimensional Emotion Evaluation in Multimodal Dialogue
arXiv:2609.39072v1 Announce Type: cross Abstract: Emotion recognition in conversation has been widely studied, but applying Large Language Models (LLMs) to continuous dimensional emotion evaluation in multimodal dialogue…
- arXiv cs.AIresearchHO-FL: Hybrid-Order Federated Learning for Heterogeneous Edge Devices
arXiv:2609.39074v1 Announce Type: cross Abstract: Federated learning (FL) on memory-constrained edge devices faces a dilemma: first-order (FO) optimization (i.e., backpropagation) demands substantial memory, whereas zero…
- arXiv cs.AIresearchRAGScope: A Leakage-Controlled, Cost-Aware Evidence-Gating Protocol for RAG Hallucination Triage
arXiv:2609.39075v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems need inexpensive ways to route generated answers: accept low-risk outputs, review uncertain ones, and reserve strong verifier…
- arXiv cs.AIresearchAssociation profile conditioning in a set-temporal transformer for cross-session intracortical motor decoding
arXiv:2609.39080v1 Announce Type: cross Abstract: Intracortical motor decoders degrade across sessions because the set of recorded units changes and persisting units can alter how their firing relates to behavior. Most e…
- arXiv cs.AIagentsCoding Agents for Coding Theory
arXiv:2609.39081v1 Announce Type: cross Abstract: We spent five weeks using an LLM coding agent on open problems in coding theory: finding large sets of four-letter words, such as DNA barcodes, that stay far apart in edi…
- arXiv cs.AIresearchTrustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail
arXiv:2609.39086v1 Announce Type: cross Abstract: Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state. Recent work shows that LLMs can generate such healing code,…
- arXiv cs.AIresearchSCIC: Scope- and Codebook-Aware Instruction Conditioning for Speaker-Adapted Expressive TTS
arXiv:2609.39088v1 Announce Type: cross Abstract: Long-form live-streaming TTS requires context-dependent prosody and paragraph-level coherence. However, many existing instruction-based TTS systems use global or uniform…
- arXiv cs.AIresearchA Generalisation Signal Need Not Be a Model-Selection Signal
arXiv:2609.39099v2 Announce Type: replace-cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When validation no…
- arXiv cs.AIagentsFalse Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents
arXiv:2609.39102v2 Announce Type: replace-cross Abstract: Self-evolving search agents build their own training curricula by jointly optimizing a proposer that generates questions and a solver that answers them. This clos…
- arXiv cs.AIresearchT-Router: Learning Thalamic Routing for Reasoning with Parameter-Efficient Reinforcement Learning
arXiv:2609.39109v1 Announce Type: cross Abstract: Parameter-efficient reinforcement learning aims to improve reasoning with a compact trainable interface to a pretrained model. We introduce the Thalamic Router (T-Router)…
- arXiv cs.AIresearchBlackout vs. Freeze: Analyzing Physical Failure Modes of VLAs under Camera Faults
arXiv:2609.39145v1 Announce Type: cross Abstract: Unreliable visual inputs can harm task performance and cause potential physical safety risks for vision-language-action (VLA) models. We analyze how $\pi 0.5$ and GR00T m…
- arXiv cs.AIagentsDAGent: Evaluate-then-Grow Planning for Deep Research Agents
arXiv:2609.39154v1 Announce Type: cross Abstract: Deep research tasks require agents to navigate large knowledge spaces, synthesize evidence across many sources, and adapt their plans as findings emerge. Directed acyclic…
- arXiv cs.AIresearchMEND: Label-Free Detection, Localisation, and Correction of Latent Hallucination in World Models
arXiv:2609.39182v1 Announce Type: cross Abstract: World Models are appearing as the next major frontier in computer vision. However, their robustness is currently largely unexplored. We identify the phenomenon of halluci…
- arXiv cs.AIresearchUniAE-MoE: A Unified Audio Encoder via Mixture of Experts
arXiv:2609.39199v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) rely on effective audio encoders for multi-task performance. We introduce UniAE-MoE, a unified audio encoder designed to model…
- arXiv cs.AIresearchIn a Streaming World, Should You Stand Still? A Comprehensive Benchmark of Anomaly Detection in Streams
arXiv:2609.39215v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) is increasingly deployed in streaming settings, where data arrive sequentially and may exhibit non-stationarity. As a result, several…
- arXiv cs.AIresearchEmergent Multi-View Geometry Through Self-Distillation
arXiv:2609.39227v1 Announce Type: cross Abstract: Over a century ago, Henri Poincar\'e argued that a motionless observer cannot acquire the notion of space. Yet, most visual representation learning methods operate on ind…
- arXiv cs.AIresearchRAIM: Robust Aggregation of Inexpensive Models for Hallucination Detection
arXiv:2609.39229v1 Announce Type: cross Abstract: Automatic evaluation of faithfulness increasingly relies on a large language model acting as a judge, yet the most reliable judges are proprietary frontier models, costly…
- arXiv cs.AIresearchWhat Streaming Anomaly Detection Finds (and Misses) in Industrial Time Series
arXiv:2609.39232v1 Announce Type: cross Abstract: EDF relies on continuous monitoring of its power plants to detect anomalies as soon as they occur. Given the absence of a universally optimal streaming method in unsuperv…
- arXiv cs.AIresearchTrust the Critic More
arXiv:2609.39247v2 Announce Type: replace-cross Abstract: Standard language model RL algorithms credit every token of a long rollout with the same advantage determined by the terminal reward. Actor-critic methods can pro…