AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsCodoku: Renewable Program-Reasoning Challenges for Frontier Coding Agents
arXiv:2609.34661v1 Announce Type: cross Abstract: Existing program-reasoning benchmarks ask large language models to predict a program's behavior on a given input. Coding agents break two assumptions on which these bench…
- arXiv cs.AIresearchEvidence-Aligned Multimodal On-Policy Self-Distillation for Fine-Grained Visual Understanding
arXiv:2609.34672v1 Announce Type: cross Abstract: Fine-grained visual understanding requires models to recognize small details within complex images. Multimodal on-policy self-distillation (OPSD) addresses this challenge…
- arXiv cs.AIresearchLearning What to Recall: Adaptive Multi-Cue Episodic Memory for World Models
arXiv:2609.34677v1 Announce Type: cross Abstract: World models predict future observations from current experience and actions, yet prediction can depend on observations seen far in the past. Episodic memory preserves pa…
- arXiv cs.AIresearchFair Fact-Checking: Closing the Cross-Lingual Gap in LLM Factual Judgement with RoSh
arXiv:2609.34678v1 Announce Type: cross Abstract: Misinformation on social media remains a critical problem, and more and more people settle it by asking a language model instead of a fact checker. Whether models judge s…
- arXiv cs.AIagentsFrom Preference to Reciprocity: Decentralized Matching with Empirically Grounded LLM-agent Based Modeling
arXiv:2609.34679v1 Announce Type: cross Abstract: Bipartite matching is a fundamental problem in game theory and market design. Classical approaches such as Gale--Shapley assume complete preferences and centralized compu…
- arXiv cs.AIresearchUsing LLMs to Detect LLM-Generated Texts: A Cross-Generation Analysis
arXiv:2609.34691v1 Announce Type: cross Abstract: Automated detection of LLM-generated texts (LGTs) is critical, yet dedicated detectors often struggle to generalize across domains and models. While general-purpose LLMs…
- arXiv cs.AIresearchSufficiency of Zeroth-Order Reward Shaping for Policy Gradient in Stabilization Control
arXiv:2609.34695v1 Announce Type: cross Abstract: Reward shaping is fundamental to modern robotic control with deep reinforcement learning (RL), yet practitioners still rely heavily on heuristic principles borrowed from…
- arXiv cs.AIresearchTriangular Resampling for Long-Horizon Motion Generation
arXiv:2609.34697v2 Announce Type: replace-cross Abstract: We introduce Triangular Resampling (TR), a post-training method for mitigating long-horizon error accumulation in motion diffusion models. Built on FloodDiffusion…
- arXiv cs.AIresearchDynamic Flow, Static Graph: KV Cache Reuse for Efficient LLM Serving on Mobile NPUs
arXiv:2609.34727v1 Announce Type: cross Abstract: On-device large language model (LLM) serving is a cornerstone of local-first personal intelligence, offering users data sovereignty, strong privacy guarantees, and freedo…
- arXiv cs.AIresearchBeyond Token Alignment: Event Completion for Cross-Tokenizer On-Policy Distillation
arXiv:2609.34738v1 Announce Type: cross Abstract: On-policy distillation (OPD) transfers knowledge between language models through teacher supervision on student-generated trajectories. With different tokenizers, a singl…
- arXiv cs.AIresearchPredictive Dual Smoothing for Column Generation
arXiv:2609.34740v1 Announce Type: cross Abstract: Solving large-scale linear programs efficiently is an important challenge in many optimization settings. A key technique is column generation, which alternates between so…
- arXiv cs.AIresearchNo Pain, More Gain: Iterative Merging for Effective Multi-Teacher On-Policy Distillation
arXiv:2609.34745v1 Announce Type: cross Abstract: Multi-teacher on-policy distillation (MOPD) combines independently developed domain teachers into a single student by distilling their predictions on student-generated sa…
- arXiv cs.AIagentsCoDrive: Cross-Vehicle World-Consistent Video Generation with Precise Trajectory Control for Cooperative Driving
arXiv:2609.34749v1 Announce Type: cross Abstract: Real-world driving is inherently multi-agent, yet most existing driving world models generate observations from a single ego vehicle. Independently extending them to mult…
- arXiv cs.AIresearchA Unifying Framework of Concept-based Explainable AI with Completeness Guarantees
arXiv:2609.34750v1 Announce Type: cross Abstract: Concept-based explanations describe neural network predictions through human-understandable properties of inputs called concepts. The field encompasses approaches that di…
- arXiv cs.AIresearchWeaveData: A Multimodal Data Analysis System with Self-Critiquing and Self-Evolving LLM Plans
arXiv:2609.34764v1 Announce Type: cross Abstract: Multimodal data analysis, which answers questions over relational tables, text, and images, has attracted growing attention in the data management community. Large langua…
- arXiv cs.AIagentsLongPuzzleBench: Evaluating GUI Agents on Long-Horizon Visual Puzzles
arXiv:2609.34769v1 Announce Type: cross Abstract: GUI agents need long-horizon visual reasoning: they must interpret a changing interface while keeping a multi-step plan viable as earlier actions constrain later ones. Ex…
- arXiv cs.AIresearchWhen VLMs Trust Context: Evaluating Scene Text Recognition under Misleading Context
arXiv:2609.34781v1 Announce Type: cross Abstract: Vision-language models (VLMs) can read text in natural scenes, but their predictions may be influenced by the surrounding context. When the printed text conflicts with wh…
- arXiv cs.AIresearchCoHuB: A Simulation Benchmark for Multi-Humanoid Collaboration
arXiv:2609.34782v1 Announce Type: cross Abstract: Many physical tasks in human environments require collaboration, from assisting a partner to jointly manipulating an object. Yet, existing humanoid benchmarks largely foc…
- arXiv cs.AIagentsCoSec: Benchmarking Agent Security in Communities
arXiv:2609.34790v4 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community boundaries may remain fix…
- arXiv cs.AIresearchESTHER: Egocentric Stereo Hand Estimation and Reconstruction in the Wild
arXiv:2609.34817v2 Announce Type: replace-cross Abstract: Human dexterity is guided by two eyes watching two hands: binocular vision supplies the metric 3D structure that fine-grained manipulation consumes. Egocentric st…
- arXiv cs.AIresearchGaussian Neural Networks
arXiv:2609.34825v1 Announce Type: cross Abstract: Gaussian neural networks (GaNNs) are proposed as a novel regularization mechanism for neural networks. From a Bayesian perspective standard regularization techniques can…
- arXiv cs.AIagentsDivOPD: Spread Wide, Look Close for Asynchronous On-Policy Distillation of Multi-turn Agents
arXiv:2609.34838v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains student agents through teacher supervision on their own interactions with an environment. However, in asynchronous multi-turn training…
- arXiv cs.AIresearchEviSplat: Preserving Multi-View Evidence in 3D Gaussian Splatting for Open-Vocabulary Segmentation
arXiv:2609.34853v1 Announce Type: cross Abstract: Open-vocabulary 3D scene understanding enables object localization and segmentation from free-form text queries without a fixed category vocabulary. Many recent methods b…
- arXiv cs.AIresearchBeyond Verbalized Confidence: Calibrating Reasoners with Differentiable Readouts
arXiv:2609.34857v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) trains reasoning models to produce correct answers, but does not ensure that their stated confidence is calibrated.…
- arXiv cs.AIagentsAttention-based Hierarchical Variational Information Bottleneck for Robust Multi-Agent Communication under Variable Bandwidth
arXiv:2609.34860v1 Announce Type: cross Abstract: Learning-based multi-agent communication under limited bandwidth does not only require deciding what to communicate, but also structuring messages so that partial transmi…
- arXiv cs.AIresearchFrom Attention Sensitivity to Layer Role: Revisiting Mixed-Precision Quantization of Transformers
arXiv:2609.34866v1 Announce Type: cross Abstract: Most post-training quantization pipelines fit each weight matrix to its pretrained counterpart, one matrix at a time. Whether that proxy tracks what an attention block ac…
- arXiv cs.AIresearchReference-Tail Trust:Certified Probability Floors for Learned Updates Inside a Deployed Network
arXiv:2609.34904v1 Announce Type: cross Abstract: Graph neural networks (GNNs) need to exploit improved message passing without surrendering control over predictions already trusted in deployment. We introduce Reference-…
- arXiv cs.AIresearchSincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Living
arXiv:2609.34907v1 Announce Type: cross Abstract: Bathroom acoustic-event recognition can support ambient assisted living in settings where continuous video monitoring is undesirable. However, practical deployment requir…
- arXiv cs.AIresearchDon't Throw Away the Tail: Action Upcycling for Policy Acceleration
arXiv:2609.34911v2 Announce Type: replace-cross Abstract: Modern robot policies predict a chunk of future actions from a single observation, execute only a prefix, and discard the rest before replanning. Choosing the len…
- arXiv cs.AIresearchDrug-Target Interaction Prediction via Hierarchical Sequential Cross-Attention over Chemical and Protein Language Models
arXiv:2609.34921v1 Announce Type: cross Abstract: Predicting Drug-Target Interactions~(DTIs) is a central task in computational drug discovery, with direct applications in virtual screening, drug repurposing, and therape…
- arXiv cs.AIagentsAudit the Scaffold, Not the Checkpoint: A Stationarity Dichotomy for Recursive Self-Improvement in Agentic Coding
arXiv:2609.34924v1 Announce Type: cross Abstract: An auditor who checks whether a system's weights are frozen is checking the wrong thing. Our stationarity dichotomy says that iterative self-modification hits strict dimi…
- arXiv cs.AIresearchJazzSAMBA: A Synchronous and Asynchronous Multi-take Band Audio Dataset of Jazz Standards for Live Music Models
arXiv:2609.34931v1 Announce Type: cross Abstract: Machine learning has made strong progress on music tasks, both as assistive tools and as creative partners. However, most systems train on multitrack corpora that emphasi…
- arXiv cs.AIresearchJevVibe: Efficient Classification-Guided Secure Code Generation
arXiv:2609.34963v1 Announce Type: cross Abstract: Large language models can generate functionally correct code that still contains security weaknesses, motivating repair pipelines that first diagnose a weakness type befo…
- arXiv cs.AIresearchCyclostationary Phase Conditioning for Medical Time Series Diffusion
arXiv:2609.34965v2 Announce Type: replace-cross Abstract: Many physiological time series, such as cardiac and brain recordings, exhibit cyclostationarity: their statistics vary periodically with an underlying cycle phase…
- arXiv cs.AIresearchSemantic Uncertainty Quantification Needs Factual Equivalence
arXiv:2609.34967v1 Announce Type: cross Abstract: Semantic uncertainty quantification for large language models rests on a common template: sample several answers, measure how much they agree, and treat disagreement as u…
- arXiv cs.AIresearchRoboFL: Federated Expert Assembly for World Action Models
arXiv:2609.34968v1 Announce Type: cross Abstract: Vision-language-action and world-action models are increasingly popular, yet remain bottlenecked by physical interaction data that is scarce, institutionally siloed, and…
- arXiv cs.AIresearchJust MLPs: Efficient Visual State Reconstruction for Multimodal Language Models
arXiv:2609.34972v1 Announce Type: cross Abstract: Long visual token sequences often account for a substantial fraction of the computational overhead in multimodal large language models~(MLLMs). Existing approaches reduce…
- arXiv cs.AIresearchSPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models
arXiv:2609.34977v1 Announce Type: cross Abstract: Multimodal Large Language Models face significant efficiency challenges that stem from two distinct yet coupled sources: data redundancy and computational redundancy. Whi…
- arXiv cs.AIresearchComposable Decoding on the Probability Simplex: Theory and Implementation
arXiv:2609.34992v1 Announce Type: cross Abstract: Decoding for large language models is typically treated as a collection of isolated sampling strategies, with limited theoretical understanding of the behaviours they ind…
- arXiv cs.AIresearchStill There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models
arXiv:2609.35002v1 Announce Type: cross Abstract: Visual token compression reduces the inference cost of Large Vision-Language Models (LVLMs). However, aggregate robustness measures do not reveal whether a particular adv…
- arXiv cs.AIresearchLearning to Act under Visual Interruptions with Vision-Language-Action Models
arXiv:2609.35003v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have demonstrated strong capabilities in robotic manipulation, but they are typically developed and evaluated with all camera streams…
- arXiv cs.AIresearchAddressing Spatial Indistinguishability in Spatiotemporal Prediction via Optimal Transport-Guided Masking
arXiv:2609.35021v1 Announce Type: cross Abstract: Spatiotemporal prediction aims to learn discriminative representations from correlated temporal signals over spatial structures for accurate future inference. A central c…
- arXiv cs.AIresearchVEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation
arXiv:2609.35028v1 Announce Type: cross Abstract: Large language models (LLMs) have made misinformation inexpensive to produce but not to verify, creating a growing asymmetry in the information ecosystem. Under tight tim…
- arXiv cs.AIagentsPEAR: Progressive Evidence-Based AutoResearch for Industrial Search Systems
arXiv:2609.35031v1 Announce Type: cross Abstract: AutoResearch improves systems through iterative experimentation: agents propose candidate modifications, evaluate them, and use the results to guide subsequent exploratio…
- arXiv cs.AIresearchBA-DPO: Bias-Adjusted Direct Preference Optimization for Language Model Alignment
arXiv:2609.35044v1 Announce Type: cross Abstract: Preference-based alignment methods such as Direct Preference Optimization (DPO) use pairwise preferences labeled by human annotators to fine-tune language models. However…
- arXiv cs.AIresearchEMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning
arXiv:2609.35047v1 Announce Type: cross Abstract: A robot should be able to learn through experiments how unfamiliar objects behave and interact, then plan with that knowledge. It need not start from scratch: physics eng…
- arXiv cs.AIresearchOPIS: An Input-Grounded Benchmark for Multi-Object Memory in Video World Models
arXiv:2609.35052v2 Announce Type: replace-cross Abstract: Video world models must preserve the visual state of the world over time, but existing evaluation protocols often rely on generated histories, video reference, or…
- arXiv cs.AIagentsTIDE: Teacher-Student Transition via Informative Distillation and Exploration for Agentic RL
arXiv:2609.35058v1 Announce Type: cross Abstract: Effective multi-turn agents require interaction strategies that coordinate information gathering, actions, and feedback over long horizons. GRPO is a reinforcement learni…
- arXiv cs.AIresearchTempoKV: Timely Staging of LLM KV Caches for Memory-Semantic Flash
arXiv:2609.35065v1 Announce Type: cross Abstract: Reusable prefix key-value (KV) caches can outgrow GPU memory in large language model (LLM) serving. A memory-semantic flash hierarchy offers SSD-backed capacity with a li…
- arXiv cs.AIresearchEchoes of Deeds: Moral History Can Shape and Steer LLM Behavioral Choices
arXiv:2609.35070v1 Announce Type: cross Abstract: Evaluations of Large Language Models (LLMs) morality typically consider decisions in isolation, thus overlooking whether an individual's unrelated prior conduct influence…