AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchProportional Representation in Temporal Voting with Ranked Preferences
arXiv:2609.30555v1 Announce Type: cross Abstract: We study proportional representation in temporal voting, where one candidate is selected in each round. While prior work has focused on approval ballots, we consider rank…
- arXiv cs.AIagentsAuditing Latent-Space Monitors for Autonomous Driving
arXiv:2609.30557v1 Announce Type: cross Abstract: Runtime failure monitors can use a model's internal representations to anticipate failures. We audit this monitoring strategy across two autonomous-driving tasks: online…
- arXiv cs.AIagentsProbing Stability-Plasticity Tradeoffs in Agent Memory through Cognitive Experimental Paradigms
arXiv:2609.30558v1 Announce Type: cross Abstract: Agent memory systems are increasingly used to maintain long-term user preferences, task states and evolving facts, but current evaluations often collapse memory behavior…
- arXiv cs.AIresearchAction Forcing: Training World Models on Unsupervised Video by Recovering Underlying Egomotion Bases
arXiv:2609.30595v1 Announce Type: cross Abstract: Synchronised action annotations are needed to train controllable world models and these datasets remain elusive. Existing approaches make use of instrumented platforms wi…
- arXiv cs.AIagentsThe Hard Part Comes After Search: Benchmarking Web Agents on Synthesizing, Organizing, and Displaying Knowledge
arXiv:2609.30604v1 Announce Type: cross Abstract: Existing computer-use agent benchmarks do not fully evaluate agents acting as assistants. A useful assistant retrieves information across complex, multi-step workflows, s…
- arXiv cs.AIresearchMedTokenBudget: Lesion-Preserving Token Routing for Dermoscopic Image Classification
arXiv:2609.30613v1 Announce Type: cross Abstract: Dermoscopy classifiers built on Vision Transformers process all image patches uniformly, although diagnostic evidence is concentrated in the lesion region. Existing token…
- arXiv cs.AIagentsSubjects, Not Authors: The Authorship Hazard in Agentic Dataspaces
arXiv:2609.30614v2 Announce Type: replace-cross Abstract: Dataspace connectors decide whether a transfer may occur, not what the transferred value contains, tolerable for contracted applications, not for LLM agents that…
- arXiv cs.AIagentsA Framework for Identifying, Categorizing, and Explaining Bias in AI-Generated Code
arXiv:2609.30642v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become integrated into software development workflows, concerns regarding unintentional biases in AI-generated code. Although evidence sug…
- arXiv cs.AIagentsCausal Retention in Interactive Agents: Interface Factorization and Selective Adaptation
arXiv:2609.30650v1 Announce Type: cross Abstract: Task performance need not determine which intervention mechanism an agent retains. We study causal retention: whether a frozen learned state answers a mechanism-probe map…
- arXiv cs.AIagentsThreat-Aware Energy-Efficient Deployment for Dynamic UAV Networks: A Multi-Agent RL Approach
arXiv:2609.30690v1 Announce Type: cross Abstract: Ensuring operational safety in threat-prone environments remains a critical challenge for multi-UAV networks serving as aerial base stations. This paper proposes an effic…
- arXiv cs.AIresearchSAGE: Source-Anchored Guidance via Frequency Equalization for Hierarchical RGB-T Alignment and Fusion
arXiv:2609.30703v1 Announce Type: cross Abstract: Spatial misregistration and cross-modal discrepancies often cause ghosting, structural blurring, and content imbalance in RGB-T fusion. Existing methods typically decoupl…
- arXiv cs.AIresearchCombining General and Domain-Specific Pretext Tasks for Brain MR Image Segmentation
arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models rely heavily on label…
- arXiv cs.AIresearchVLALight: Lightweight Vision-Language-Action Models for Emergency-Aware Traffic Signal Control
arXiv:2609.30709v1 Announce Type: cross Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretation of intersection s…
- arXiv cs.AIresearchWords Speak Louder Than Order: A Behavioral Evaluation of Gemma 4
arXiv:2609.30716v1 Announce Type: cross Abstract: When a language model receives two conflicting documents as input, how does it decide which one to prioritize? Does it rely on how the sources are framed or the presentat…
- arXiv cs.AIresearchWerracle: Sub-Cent Intra-Block AI Reflex Oracles and Flash-Loan Circuit Breakers for EVM Smart Contracts
arXiv:2609.30719v1 Announce Type: cross Abstract: Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural weight matrices ins…
- arXiv cs.AIresearchTrafficImag: A Benchmark for Counterfactual Roadside Traffic Video Generation
arXiv:2609.30722v1 Announce Type: cross Abstract: Existing roadside traffic datasets support perception, forecasting, and visual question answering, but they do not evaluate counterfactual video generation, in which a se…
- arXiv cs.AIresearchAnatomy-Aware Dexterity-Driven Design Optimization of Surgical Continuum Robots
arXiv:2609.30745v1 Announce Type: cross Abstract: Performing complex medical procedures with continuum robots requires careful selection of their geometric design parameters. The robot should have high dexterity in the s…
- arXiv cs.AIresearchBeyond the Last Truffula Tree: SustainAI - A Water-Aware, Closed-Loop Framework for Environmentally Accountable AI
arXiv:2609.30747v1 Announce Type: cross Abstract: As artificial intelligence (AI) becomes embedded in everyday life, its environmental footprint, particularly water consumption remains largely invisible. While energy and…
- arXiv cs.AIresearchNavGen: Visual Generative Models as a Scalable Data Engine for Embodied 3D Navigation
arXiv:2609.30770v1 Announce Type: cross Abstract: General-purpose robot models increasingly rely on large and diverse datasets. For embodied 3D navigation, however, existing data sources face a fundamental trade-off: sim…
- arXiv cs.AIagentsSkip the Talk, Re-Focus on Vision: Latent Reasoning for Reasoning Segmentation in Multimodal Large Language Models
arXiv:2609.30783v1 Announce Type: cross Abstract: Reasoning segmentation aims to interpret implicit textual queries and enable fine-grained visual perception, which is critical for applications such as human-computer int…
- arXiv cs.AIresearchXPhysICS: Cross-Physical-Domain Threat Grounding for Industrial Control Systems Security
arXiv:2609.30805v2 Announce Type: replace-cross Abstract: Industrial control system attacks are usually documented in terms of the plant where they occurred: its sensors, actuators, process stages, and control logic. Yet…
- arXiv cs.AIagentsEvaluation Is All You Need for Multi-Modal Autonomous Driving
arXiv:2609.30818v1 Announce Type: cross Abstract: Multi-modal planning is promising for autonomous driving by representing multiple plausible behaviors in ambiguous and long-tail scenarios. Existing methods mainly focus…
- arXiv cs.AIresearchSubject-Invariant Cross-Modal Decoding of Perceived Speech from Brain Recordings
arXiv:2609.30832v1 Announce Type: cross Abstract: Perceived speech decoding based on non-invasive brain-computer interface (BCI) signals has been extensively studied in recent years. Research in this field primarily face…
- arXiv cs.AIresearchMOPD-Router: Rethinking Teacher Routing in Multi-Teacher On-Policy Distillation
arXiv:2609.30837v2 Announce Type: replace-cross Abstract: Multi-teacher on-policy distillation (MOPD) integrates specialized capabilities into a single student, but existing practice typically hard-routes each prompt to…
- arXiv cs.AIagentsDeveloping a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development
arXiv:2609.30863v1 Announce Type: cross Abstract: The emergence of AI agents is expected to reshape software engineering by moving beyond AI as assistants towards systems capable of planning, executing, and evaluating de…
- arXiv cs.AIresearchPersistent Negatives for Adversarial Black-Box On-Policy Distillation
arXiv:2609.30864v1 Announce Type: cross Abstract: Black-box On-Policy Distillation (OPD) seeks to improve a student from its own generations when the teacher provides sampled responses but not token probabilities. Advers…
- arXiv cs.AIagentsWarned alike, AI agents avoid the less-crowded road while people take it
arXiv:2609.30883v1 Announce Type: cross Abstract: AI agents built on a few shared models increasingly act for many people. A shared forecast about others can align their choices and change how scarce capacity is allocate…
- arXiv cs.AIresearchAdaptive Pilot Selection for Unified Semantic Communication and Semantic Sensing in ISAC
arXiv:2609.30891v1 Announce Type: cross Abstract: Semantic communication (SemCom) and integrated sensing and communication (ISAC) are promising technologies for future 6G wireless networks. Existing studies have applied…
- arXiv cs.AIresearchRobust to Which Model Change? A Unified Evaluation of Robust Counterfactual Explanations
arXiv:2609.30918v2 Announce Type: replace-cross Abstract: Robust counterfactual explanations promise recourse that still works after the model behind it changes. Whether they keep that promise depends on what the change…
- arXiv cs.AIresearchUltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasound
arXiv:2609.30928v1 Announce Type: cross Abstract: Ultrasound is one of the most widely used medical imaging modalities, and recent large vision-language models(VLMs) have shown increasing capabilities in ultrasound image…
- arXiv cs.AIresearchEstimating and Orthogonalizing Unknown Pre-training Gradients for Continual Fine-tuning of Large Language Models
arXiv:2609.30935v1 Announce Type: cross Abstract: Continual fine-tuning is essential for large language models (LLMs) to dynamically adapt to real-world environments, yet it inevitably suffers from catastrophic forgettin…
- arXiv cs.AIresearchSpackle: Completing Large View Single Image NVS with Adaptive Gaussians
arXiv:2609.30941v1 Announce Type: cross Abstract: Single-image novel view synthesis (NVS) enables photorealistic rendering of un- observed viewpoints from a single input. Practical NVS systems require two key capabilitie…
- arXiv cs.AIresearchOneWorld: Learning Consistent Physics Across Actions in World Models
arXiv:2609.30946v1 Announce Type: cross Abstract: Action-conditioned video world models aim to predict scene evolution under different actions, a capability that is essential for reliable planning, decision-making, and i…
- arXiv cs.AIresearchPORL: Pretrained Offline Reinforcement Learning for the Job Shop Scheduling Problem
arXiv:2609.30948v1 Announce Type: cross Abstract: The Job Shop Scheduling Problem (JSSP) is a fundamental combinatorial optimization problem in industrial optimization. This work introduces Pretrained Offline Reinforceme…
- arXiv cs.AIresearchMVVBench: Benchmarking 4D Reasoning in Vision-Language Models
arXiv:2609.30952v1 Announce Type: cross Abstract: Multi-view video understanding requires integrating spatial and temporal evidence across multiple, often non-overlapping camera streams: tracking entities as they transit…
- arXiv cs.AIresearchDoes Uniform Discrete Diffusion Need Time?
arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this paper, we first show t…
- arXiv cs.AIresearchFARE: Forensic Acceptance Region Estimation for Catching Bait-and-Switch Image Generators
arXiv:2609.30982v1 Announce Type: cross Abstract: Modern AI image generators are increasingly deployed as opaque APIs, where customers can query the deployed service, but cannot inspect model weights or architecture. Thi…
- arXiv cs.AIresearchFLIP: Final Layer Inference-Time Probing for Vision-Language Models
arXiv:2609.30993v2 Announce Type: replace-cross Abstract: We present FLIP, a final-layer inference-time probe for testing whether a logit-facing intervention site in an open-weight vision-language model (VLM) supports st…
- arXiv cs.AIresearchThe Linear Representation Hypothesis for Vision-Language-Action Models
arXiv:2609.30996v2 Announce Type: replace-cross Abstract: The linear representation hypothesis (LRH) has become a standard lens for measuring and intervening on semantic information through the internal representations o…
- arXiv cs.AIresearchCan Pixels Alone Reveal Image Origin? Minimax Limits and Learnable Interfaces for Passive Provenance
arXiv:2609.30997v1 Announce Type: cross Abstract: Passive image provenance asks whether pixels alone can reveal where an image came from: a human, an aggregate AI class, or a particular generator. This becomes a robustne…
- arXiv cs.AIresearchG$^2$PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation
arXiv:2609.31009v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is a practical approach to reducing the memory and computational footprint of large language models (LLMs) without retraining. GPTQ-based…
- arXiv cs.AIagentsDynBranch: Speculative Subgraph Reuse for Dynamic Agentic LLM Serving
arXiv:2609.31047v1 Announce Type: cross Abstract: Agentic LLM workflows decide their execution paths at runtime. Downstream computation may be predictable, or may have run before, yet it cannot begin until the model or t…
- arXiv cs.AIresearchQuantum Diffusion Models for Medical Image Analysis
arXiv:2609.31070v1 Announce Type: cross Abstract: Quantum Machine Learning is a novel field of research aimed at devising machine learning approaches exploiting principles of quantum mechanics, such as superposition, ent…
- arXiv cs.AIresearchDepthEvidence: Unifying Metric Depth Prediction and Geometric Reasoning in Multimodal Language Models
arXiv:2609.31103v1 Announce Type: cross Abstract: Spatial reasoning with metric constraints requires linking objects to geometric measurements and preserving their numerical content during language reasoning. We present…
- arXiv cs.AIresearchBayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
arXiv:2609.31107v2 Announce Type: replace-cross Abstract: We study Bayesian optimization (BO) through the lens of information geometry. Pulling back the Fisher information metric through the surrogate posterior map yield…
- arXiv cs.AIresearchFrom Shortcut Learning to Discrete Neural Insertion Sort
arXiv:2609.31114v1 Announce Type: cross Abstract: Neural algorithmic reasoning aims to train neural networks to follow known algorithms and generalize beyond the input sizes seen during training. However, correct final o…
- arXiv cs.AIresearchPocket-STVG: lightweight architecture for Spatio-Temporal Video Grounding
arXiv:2609.31135v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to localize the spatio-temporal tube in a video corresponding to a natural language query. While recent methods achieve strong…
- arXiv cs.AIresearchJevAdvBench: A Benchmark and Black-Box Attacks for Reinforcement Learning for Calibrated Decisions Models
arXiv:2609.31142v2 Announce Type: replace-cross Abstract: Typed decision models (TDMs), such as Jev, answer a question about an input with a probability, an option, or an ordinal level. Web services execute these decisio…
- arXiv cs.AIresearchFedHisto-PAST: Parameter-Efficient Stain-Aware Federated Learning for Cross-Site Lung Histopathology Classification
arXiv:2609.31150v1 Announce Type: cross Abstract: Cross-site lung histopathology classification must account for stain variation, non-IID client data, missing classes, and the cost of adapting large pathology encoders. T…
- arXiv cs.AIresearchTeacher-Anchored Selection of Post-Training Quantized Models under Domain Shift
arXiv:2609.31155v1 Announce Type: cross Abstract: Compressing a trained model yields a family of deployment candidates, and under domain shift the most compressed one need not be the one to deploy. We study selection ove…