AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchVLAQuantBench: Closed-Loop Evaluation of Post-Training Quantization for Vision-Language-Action Models
arXiv:2609.25376v1 Announce Type: cross Abstract: Post-training quantization reduces the memory requirements of vision-language-action (VLA) models, but precision selection must account for the interaction between layer…
- arXiv cs.AIresearchPICPIs: Prediction-Interval-Conditional Prediction Intervals
arXiv:2609.25388v2 Announce Type: replace-cross Abstract: A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal prediction in…
- arXiv cs.AIagentsPasses Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development
arXiv:2609.25396v1 Announce Type: cross Abstract: Parallel coding agents can produce patches that work alone but fail when merged. This happens when one agent changes an interface or rule that another agent still relies…
- arXiv cs.AIresearchDeep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing
arXiv:2609.25397v1 Announce Type: cross Abstract: The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and manufacturing to c…
- arXiv cs.AIagentsBeyond Natural Language: An Agent-Native Language for Autonomous Science
arXiv:2609.25421v1 Announce Type: cross Abstract: As autonomous AI agents take on every stage of scientific inquiry, research output is expanding far beyond human review capacity. Yet scientific communication still relie…
- arXiv cs.AIagentsPredictive Uncertainty for Neural CAE Surrogates
arXiv:2609.25430v1 Announce Type: cross Abstract: Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that remain meaningful a…
- arXiv cs.AIresearchLightweight Ranking Heads: Accelerating Multi-Task Experimentation in Production Recommender Systems
arXiv:2609.25433v1 Announce Type: cross Abstract: Modern production-scale recommender systems rely on complex, multi-task ranking models. Introducing new prediction tasks into these massive systems often causes bottlenec…
- arXiv cs.AIagentsTransformer-Informed Trajectory Optimization for Relative Motion in Cislunar Orbits
arXiv:2609.25460v1 Announce Type: cross Abstract: Autonomous spacecraft guidance and control requires a fast solution to non-convex trajectory optimization, which can be accelerated by providing a near-optimal initial gu…
- arXiv cs.AIresearchA Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization
arXiv:2609.25471v1 Announce Type: cross Abstract: Semi-supervised federated learning (SSFL) trains models on clients' unlabeled data using a teacher to generate pseudo-labels, with a small labeled seed dataset on the ser…
- arXiv cs.AIresearchTerminal Shrinkage Averaging Reveals a Schedule-Estimator Interaction in LLM Pretraining
arXiv:2609.25482v1 Announce Type: cross Abstract: Large language model (LLM) pretraining conventionally returns the raw final iterate. This couples two design choices: the learning-rate schedule that generates the parame…
- arXiv cs.AIresearchRGSQ: Riemannian Geometry-Sensitive Quantization for Large Vision-Language Models
arXiv:2609.25492v1 Announce Type: cross Abstract: Large vision-language models (VLMs) can be efficiently deployed under stringent memory and latency constraints through post training quantization (PTQ). However, most PTQ…
- arXiv cs.AIresearchUniversal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains
arXiv:2609.25498v2 Announce Type: replace-cross Abstract: Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessive energy di…
- arXiv cs.AIresearchHill Sampling for Test-Time Scaling: A Simple and Better Alternative to Repeated Sampling, Evolution, and Training
arXiv:2609.25510v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can improve solutions to verifiable scientific and algorithmic problems by spending additional computation at test time. Recent syste…
- arXiv cs.AIresearchWest-WRF AI 2-km: High-Resolution Prediction of Integrated Vapor Transport and Precipitation
arXiv:2609.25512v1 Announce Type: cross Abstract: We introduce a stretched-grid artificial intelligence (AI) weather forecasting model with 2-km resolution over the western United States and part of the Northeast Pacific…
- arXiv cs.AIresearchCompressing Long Context into Answer-Aligned Memory Embeddings for LLM Inference
arXiv:2609.25537v1 Announce Type: cross Abstract: Large language model (LLM) inference is constrained by the quadratic scaling of self-attention and the linear scaling of the KV cache, increasing latency, energy consumpt…
- arXiv cs.AIresearchA JEPA Recipe for Tabular Foundation Models
arXiv:2609.25541v1 Announce Type: cross Abstract: Tabular foundation models learn to predict cell values in context, whereas world-model self-supervision asks for prediction in representation space (LeCun, 2022; Assran e…
- arXiv cs.AIresearchDefaultGNN: A Dual-Perspective GNN Framework for Predicting Corporate Default from Buyer-Seller Transaction Networks
arXiv:2609.25542v1 Announce Type: cross Abstract: Corporate default prediction is a core problem in financial risk management, yet traditional credit models rely heavily on financial statements that are often sparse or u…
- arXiv cs.AIresearchIndustrialVLA-Bench: A Traceable Multi-Axis Evaluation of Open Robot Policy Models
arXiv:2609.25562v2 Announce Type: replace-cross Abstract: Open robot policies increasingly follow two paradigms: vision-language-action models (VLAs) directly map observations and instructions to actions, whereas world-a…
- arXiv cs.AIagentsAkasicMEM: Governed Enterprise Memory for Agents
arXiv:2609.25563v1 Announce Type: cross Abstract: Agent memory enables enterprise agents to retain knowledge acquired during work and reuse it across tasks and agents, turning execution experience into persistent organiz…
- arXiv cs.AIresearchRootQuantV2: Adapting a Vision Foundation Model for Root-Trait Regression from Minirhizotron Imagery
arXiv:2609.25567v1 Announce Type: cross Abstract: A lack of high-throughput phenotyping solutions for root traits in field-grown crops has severely constrained understanding and improvement of below-ground traits and pro…
- arXiv cs.AIresearchEMGBlend: Heterogeneity-Aware Self-Supervised Pretraining for Gesture and Force Decoding
arXiv:2609.25582v1 Announce Type: cross Abstract: Public surface electromyography (EMG) datasets vary widely in electrode layout, channel count, frequency support, and size. Simply mixing them for pretraining can misalig…
- arXiv cs.AIresearchDeflecting the Value Compass: Interacting with Large Language Models Temporarily Shifts Human Value Priorities Toward Personal Focus
arXiv:2609.25586v1 Announce Type: cross Abstract: Large language models increasingly support decisions where values are in tension, yet little is known about whether interacting with them changes which values users prior…
- arXiv cs.AIresearchWhat Should a Self-Teacher See? Privileged Context Design for On-Policy Self-Distillation
arXiv:2609.25623v2 Announce Type: replace-cross Abstract: More privileged information does not always make a better teacher. We study this tension in on-policy self-distillation (OPSD), where a self-teacher scores the st…
- arXiv cs.AIresearchAn Exploratory Replica-Overlap Probe of the Grokking Transition
arXiv:2609.25634v1 Announce Type: cross Abstract: We trained 64 independently seeded networks in four configurations, continuing each to sustained convergence or a 40,000-epoch ceiling. We then asked whether an RSB-inspi…
- arXiv cs.AIresearchWhen Quantum Meets AI: Quantum Methods for Machine Learning and Machine Learning Methods for Quantum Systems
arXiv:2609.25641v1 Announce Type: cross Abstract: This thesis studies the intersection of quantum computing and artificial intelligence in two directions: quantum methods for machine learning and machine learning methods…
- arXiv cs.AIresearchFrom Experts to Sub-experts: Fine-grained Parameter-Efficient Fine-Tuning for MoE LLMs
arXiv:2609.25655v1 Announce Type: cross Abstract: As large language models (LLMs) scale rapidly, dense full-parameter adaptation becomes increasingly expensive, motivating sparse and modular architectures such as Mixture…
- arXiv cs.AIresearchTeaching Reinforcement Learning and Humanoid Robotics to High-School Students: An Expert-Validated Curriculum Design on a Low-Cost Open Platform
arXiv:2609.25674v1 Announce Type: cross Abstract: Lower cost open source robots and reinforcement learning (RL) simulation tools create new opportunities for precollege students to engage with contemporary robotics. Howe…
- arXiv cs.AIresearchInterpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa
arXiv:2609.25697v1 Announce Type: cross Abstract: Purpose: To develop and evaluate an interpretable artificial intelligence (AI) framework for glaucoma screening from low-cost portable, handheld retinal fundus photograph…
- arXiv cs.AIresearchSlow Decay and Silenced Expression: Iterated Subliminal Trait Transfer in Language-Model Lineages
arXiv:2609.25721v1 Announce Type: cross Abstract: Language models are increasingly trained on the outputs of other models, forming chains that we call lineages, in which a trait present in one generation can pass to the…
- arXiv cs.AIresearchSelf-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe
arXiv:2609.25728v1 Announce Type: cross Abstract: Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural networks, but a central…
- arXiv cs.AIresearchBeyond Class Marginals: Bounding Rehearsal Gaps without Freezing Class Co-occurrence
arXiv:2609.25735v1 Announce Type: cross Abstract: Class-balanced replay controls class frequency but does not determine the interval between successive replay appearances of a class. We study this interval, the rehearsal…
- arXiv cs.AIresearchSyndrome, Synergy, and Safety: Structured Reasoning and Knowledge-Driven Alignment for TCM Prescription Generation
arXiv:2609.25755v1 Announce Type: cross Abstract: Applying large language models to Traditional Chinese Medicine (TCM) prescription generation reveals three clinically critical gaps: models produce end-to-end mappings wi…
- arXiv cs.AIresearchVideo-HopChain: Multi-Hop Questions and Confidence-Gated Exploration for Video Reasoning Models
arXiv:2609.25773v2 Announce Type: replace-cross Abstract: HopChain has shown on still images that multi-hop data synthesis improves vision-language reasoning, because long chain-of-thought reasoning exposes errors that c…
- arXiv cs.AIresearchEvaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models
arXiv:2609.25788v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing works often overlook…
- arXiv cs.AIresearchYou Only Need 2/3 of the Chosen Experts: An Empirical Study of Dynamic Expert Pruning in Fine-Grained MoE LLMs
arXiv:2609.25809v1 Announce Type: cross Abstract: Fine-grained mixture-of-experts (MoE) architectures have become a mainstream design for open-weight LLMs, with hundreds of experts and increasingly many selected per toke…
- arXiv cs.AIresearchMorphoSHAP: Rethinking the Unit of Attribution in Explanation for Deep Visual Models
arXiv:2609.25815v1 Announce Type: cross Abstract: Visual attribution methods typically explain predictions using pixels, superpixels, or regular patches. These representations can localize important regions, but provide…
- arXiv cs.AIagentsCogenPVG: Cognitive-Enhanced Reflective Multi-Agent Framework for Persuasive Video Generation
arXiv:2609.25821v1 Announce Type: cross Abstract: Persuasive video generation (PVG) is a valuable yet under-explored research topic. Despite the significant advances in multimodal content generation, AI-empowered automat…
- arXiv cs.AIresearchIn-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization
arXiv:2609.25836v2 Announce Type: replace-cross Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation under limit…
- arXiv cs.AIresearchEvaluating the Effectiveness of SechKAN on 1D Data
arXiv:2609.25876v1 Announce Type: cross Abstract: The connection between the Kolmogorov-Arnold representation theorem (KART) and neural network design has led to the development of Kolmogorov-Arnold Networks (KANs), with…
- arXiv cs.AIagentsRisk-Aware Online Conformal State Probing
arXiv:2609.25889v1 Announce Type: cross Abstract: AI-based autonomous agents, typically hosted at data centers, must acquire state information from robots or edge devices in order to issue informed control decisions. Man…
- arXiv cs.AIresearchBAS-OPD: Budget-Aware Selective On-Policy Self-Distillation for Fine-Grained Multimodal Perception
arXiv:2609.25891v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) often struggle with fine-grained visual perception when processing complete images, as critical evidence may only appear in local…
- arXiv cs.AIresearchToward Responsible AI-Augmented Cyber Defense: Pattern Recognition, Defense-in-Depth, and the Case for Human-AI Collaboration
arXiv:2609.25921v1 Announce Type: cross Abstract: Cybersecurity literature has extensively documented the operational benefits of artificial intelligence (AI) for threat detection, incident response, and prevention, whil…
- arXiv cs.AIresearchDestination Support Restoration for Finite-Set Multimodal Trajectory Prediction
arXiv:2609.25942v1 Announce Type: cross Abstract: Robots operating around pedestrians often reason over a finite set of predicted human futures. Repeated online updates can concentrate this limited prediction budget on d…
- arXiv cs.AIresearchInterweaving Marginals into Multivariate Sample Paths: Training-Free Dependence Construction for Probabilistic Time Series Foundation Models
arXiv:2609.25980v1 Announce Type: cross Abstract: Probabilistic time series foundation models (TSFMs) provide coordinate-wise predictive distributions, but these marginals do not determine a joint distribution over multi…
- arXiv cs.AIresearchSE-MSB: End-to-End Unpaired Speech Enhancement using Mamba Schr\"odinger Bridges
arXiv:2609.26000v1 Announce Type: cross Abstract: Speech enhancement (SE) models typically rely on supervised learning with paired data examples where clean speech is synthetically degraded. This paradigm limits performa…
- arXiv cs.AIresearchSkytopia: Monocular Drone Navigation with Action-Conditioned Latent World Models
arXiv:2609.26007v1 Announce Type: cross Abstract: Monocular drone navigation requires reaching a goal in an unseen environment from a single forward-facing camera, which offers few cues for depth and scale. World models…
- arXiv cs.AIresearchCompiling Sufficient Governance Context from Declared Losses and Reachable States: Exact Observation-Contract Synthesis with Cardinality and Cost Objectives
arXiv:2609.26016v1 Announce Type: cross Abstract: We call the object this paper derives and certifies a minimal sufficient governance context: given a finite reachable-state model, a deterministic declared verdict, and c…
- arXiv cs.AIresearchReciprocal Collaboration: how lessons from convergence in GLAMs can enhance interdisciplinary AI research
arXiv:2609.26023v1 Announce Type: cross Abstract: The need for collaboration between diverse fields of research is increasingly recognised as important by research funding agencies. A significant driver of this need is t…
- arXiv cs.AIresearchREVE: Efficient Hallucination Correction for Large Audio-Language Models via Reused Encoder States
arXiv:2609.26028v1 Announce Type: cross Abstract: Large audio-language models may mention acoustic events that are absent from the input. A separate audio event detector can verify these mentions, but doing so requires a…
- arXiv cs.AIresearchxWhyL: Causal Interactive Learning
arXiv:2609.26037v1 Announce Type: cross Abstract: Explanations are central to causal reasoning, and cognitive science has long established that the human drive to explain is itself a mechanism for learning about causalit…