AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchObscuring Data Contamination Through Translation: Evidence from Arabic Corpora
arXiv:2601.14994v2 Announce Type: replace-cross Abstract: Data contamination can invalidate benchmark evaluation when a model benefits from memorized evaluation content rather than genuine generalization. Yet contaminati…
- arXiv cs.AIresearchTrust, Don't Trust, or Flip: Robust Preference-Based Reinforcement Learning with Multi-Expert Feedback
arXiv:2601.18751v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise trajectory comparisons. How…
- arXiv cs.AIresearchFreshMem: Brain-Inspired Frequency-Space Hybrid Memory for Streaming Video Understanding
arXiv:2602.01683v2 Announce Type: replace-cross Abstract: Transitioning Multimodal Large Language Models (MLLMs) from offline to online streaming video understanding is essential for continuous perception. However, exist…
- arXiv cs.AIresearchPhantom Transfer: Data Poisoning can Survive Data-Level Defences
arXiv:2602.04899v3 Announce Type: replace-cross Abstract: We present a data poisoning attack -- Phantom Transfer -- with the property that, even if you know precisely how the poison was placed into an otherwise benign da…
- arXiv cs.AIresearchBi-temporal Image-driven Acute Stroke Evolution Analysis
arXiv:2602.07535v2 Announce Type: replace-cross Abstract: Acute ischemic stroke requires rapid treatment decisions that are strongly guided by emergency imaging. Admission computed tomography perfusion (CTP) is commonly…
- arXiv cs.AIresearchRethinking Latency Denial-of-Service: Attacking the LLM Serving Framework, Not the Model
arXiv:2602.07878v2 Announce Type: replace-cross Abstract: LLM inference is inherently expensive, even a modest slowdown can translate into substantial operating costs and severe availability risks. Recently, a growing bo…
- arXiv cs.AIresearchActionCodec: What Makes for Good Action Tokenizers
arXiv:2602.15397v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior instruction-followin…
- arXiv cs.AIresearchHistCAD: Constraint-Aware Parametric CAD Histories for Evaluating Editability
arXiv:2602.19171v4 Announce Type: replace-cross Abstract: Sketch constraints specify geometric conditions for constructing and modifying parametric CAD models. We study whether predicted constraints allow a given history…
- arXiv cs.AIresearchTest-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
arXiv:2602.22871v3 Announce Type: replace-cross Abstract: Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typically trajectory-level…
- arXiv cs.AIresearchmAVE: A Watermark for Joint Audio-Visual Generation Models
arXiv:2603.07090v2 Announce Type: replace-cross Abstract: Watermarking joint audio-visual generation supports vendor copyright protection and content provenance. However, independently valid audio and video watermarks do…
- arXiv cs.AIagents\$OneMillion-Bench: How Far are Language Agents from Human Experts?
arXiv:2603.07980v2 Announce Type: replace-cross Abstract: As language models (LMs) evolve from chat assistants to long-horizon agents capable of multi-step reasoning and tool use, existing benchmarks remain largely confi…
- arXiv cs.AIagentsArbiter: Detecting Interference in LLM Agent System Prompts
arXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to conventional software…
- arXiv cs.AIresearchJailbreak Scaling Laws for Large Language Models: Polynomial-Exponential Crossover
arXiv:2603.11331v4 Announce Type: replace-cross Abstract: Adversarial attacks can reliably steer safety-aligned large language models toward unsafe behavior. Empirically, we find that adversarial prompt-injection attacks…
- arXiv cs.AIresearchPhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization
arXiv:2603.13228v3 Announce Type: replace-cross Abstract: Recent progress in text-conditioned human motion generation has been largely driven by diffusion models trained on large-scale human motion data. Building on this…
- arXiv cs.AIresearchExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation
arXiv:2603.17524v2 Announce Type: replace-cross Abstract: We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must follow instruction-spec…
- arXiv cs.AIresearchImperative Interference: Social Register Shapes Instruction Topology in Large Language Models
arXiv:2603.25015v2 Announce Type: replace-cross Abstract: System prompt instructions that cooperate in English compete in Spanish, with the same semantic content, but opposite interaction topology. We present instruction…
- arXiv cs.AIresearchDecidable By Construction: Design-Time Verification for Truly Fearless Systems
arXiv:2603.25414v5 Announce Type: replace-cross Abstract: Concurrency, parallelism and distributed execution become truly fearless when the compiler tracks wait-for edges, proves multi-threaded work is sound and preserve…
- arXiv cs.AIresearchTask-Centric Personalized Federated Fine-Tuning of Language Models
arXiv:2604.00050v3 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising technique for training language models on distributed and private datasets of diverse tasks. However, aggregati…
- arXiv cs.AIresearchAI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services
arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done by hand. We describe…
- arXiv cs.AIresearchVirtual Smart Metering in District Heating Networks via Heterogeneous Spatial-Temporal Graph Neural Networks
arXiv:2604.10166v2 Announce Type: replace-cross Abstract: Intelligent operation of thermal energy networks aims to improve energy efficiency, reliability, and operational flexibility through data-driven control, predicti…
- arXiv cs.AIresearchIAD-Unify: Task-Specific Interfaces for Industrial Anomaly Understanding, Segmentation, and Generation
arXiv:2604.12440v3 Announce Type: replace-cross Abstract: Industrial anomaly inspection requires complementary capabilities: explaining an observed defect, localizing its pixels, and synthesizing a controlled edit. We pr…
- arXiv cs.AIresearchSparKV: Overhead-Aware KV Cache Loading for Efficient On-Device LLM Inference
arXiv:2604.21231v3 Announce Type: replace-cross Abstract: Efficient inference for on-device Large Language Models (LLMs) remains challenging due to limited hardware resources and the high cost of the prefill stage, which…
- arXiv cs.AIagentsBridging the Last Mile of Circuit Design: PostEDA-Bench, a Hierarchical Benchmark for PPA Convergence and DRC Fixing
arXiv:2605.06936v4 Announce Type: replace-cross Abstract: LLM-based agents are increasingly applied to the "last mile" of Electronic Design Automation (EDA): repairing residual sign-off Design Rule Check (DRC) violations…
- arXiv cs.AIresearchSAM 3D Animal: Promptable Animal 3D Reconstruction from Images in the Wild
arXiv:2605.07604v2 Announce Type: replace-cross Abstract: 3D animal reconstruction in the wild remains challenging due to large species variation, frequent occlusions, and the prevalence of multi-animal scenes, while exi…
- arXiv cs.AIresearchAPEX: Assumption-free Projection-based Embedding eXamination Metric for Generative Distribution Evaluation
arXiv:2605.07786v4 Announce Type: replace-cross Abstract: As generative models achieve unprecedented visual quality, the gold standard for image evaluation remains traditional feature-distribution metrics. However, these…
- arXiv cs.AIresearchDCVD: Dual-Channel Cross-Modal Fusion for Joint Vulnerability Detection and Localization
arXiv:2605.11015v2 Announce Type: replace-cross Abstract: Software vulnerability detection plays a critical role in ensuring system security, where real-world auditing requires not only determining whether a function is…
- arXiv cs.AIresearchFeatCal: Feature Calibration for Post-Merging Models
arXiv:2605.13030v2 Announce Type: replace-cross Abstract: Model merging combines task experts into one model and avoids joint training, retraining, or deploying many expert models, but the merged model often still underp…
- arXiv cs.AIresearchBeyond Accuracy: Robustness, Interpretability and Expressiveness of EEG Foundation Models
arXiv:2605.17562v2 Announce Type: replace-cross Abstract: EEG foundation models (EEG-FMs) have been evaluated predominantly on clean, in-distribution accuracy, demonstrating modest gains over supervised baselines and wea…
- arXiv cs.AIresearchSelf-Evolving Spatial Reasoning in Vision Language Models via Geometric Logic Consistency
arXiv:2605.18162v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have made striking progress, yet their spatial reasoning remains fragile. Models that answer an original input correctly can still f…
- arXiv cs.AIresearchToken by Token, Compromised: Backdoor Vulnerabilities in Unified Autoregressive Models
arXiv:2605.19227v2 Announce Type: replace-cross Abstract: Unified autoregressive models (UAMs) are transformer models that generate text as well as image tokens within a single autoregressive pass. Shared parameters and…
- arXiv cs.AIresearchWorld-Ego Modeling for Embodied Video Generation in Long-Horizon Navigation-Manipulation Tasks
arXiv:2605.19957v2 Announce Type: replace-cross Abstract: Embodied video world models typically capture both scene evolution and the robot's behavior, which we refer to as the \emph{world} and the \emph{ego}, respectivel…
- arXiv cs.AIresearch4D-GSW: Kinematic-Aware Spatio-Temporal Consistent Watermarking for 4D Gaussian Splatting
arXiv:2605.22342v2 Announce Type: replace-cross Abstract: While 4D Gaussian Splatting (4DGS) has revolutionized high-fidelity dynamic reconstruction, safeguarding the intellectual property of these assets remains an open…
- arXiv cs.AIresearchThe Distillation Game: Adaptive Evaluations & Efficient Defenses
arXiv:2605.22737v4 Announce Type: replace-cross Abstract: Distillation attacks create a deployment trade-off for model providers: the same outputs that make a model more useful can also make it easier to imitate. We stud…
- arXiv cs.AIresearchROAR: Retrieval Opportunity-Aware Refinement for Zero-Shot Time Series Forecasting
arXiv:2605.24911v2 Announce Type: replace-cross Abstract: Retrieval augmentation provides time series forecasters with historical continuations, yet even candidates that outperform the base forecast may fail to improve t…
- arXiv cs.AIagentsVISTA: An End-to-End Benchmark for Visual Spec-to-Web-App Coding Agents
arXiv:2605.26144v4 Announce Type: replace-cross Abstract: Coding agents can now build applications from design mockups, but a screen that looks right is not an application that works. Existing benchmarks either score vis…
- arXiv cs.AIresearchTrust Region Q Adjoint Matching
arXiv:2605.27079v2 Announce Type: replace-cross Abstract: Off-policy reinforcement learning of pretrained flow policies remains challenging due to the instability of optimization arising from the multi-step sampling proc…
- arXiv cs.AIresearchEfficient and Scalable Provenance Tracking for LLM-Generated Code Snippets
arXiv:2605.28510v3 Announce Type: replace-cross Abstract: Large language models (LLMs) for code completion and generation are increasingly used in software development, yet they may reproduce training examples verbatim a…
- arXiv cs.AIresearchMemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems
arXiv:2605.28732v4 Announce Type: replace-cross Abstract: Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult to debug. Tr…
- arXiv cs.AIresearchLearning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation
arXiv:2606.01833v2 Announce Type: replace-cross Abstract: Generative emulators of protein dynamics produce plausible trajectories at a fraction of the cost of molecular dynamics, but they inherit their training distribut…
- arXiv cs.AIresearchLoRi: Low-Rank Distillation for Implicit Reasoning
arXiv:2606.05315v2 Announce Type: replace-cross Abstract: Implicit chain-of-thought (iCoT) methods aim to internalize reasoning in large language models, but often underperform explicit CoT prompting. We empirically find…
- arXiv cs.AIresearchLearning to Attack and Defend: Adaptive Red Teaming of Language Models via GRPO
arXiv:2606.09701v2 Announce Type: replace-cross Abstract: Language model safety must continually adapt to evolving attacks. Recent works have demonstrated that reinforcement learning can be used to train stronger attacke…
- arXiv cs.AIagentsRight Family, Wrong Skill: Evaluating Risk Exposure in Agent Skill Retrieval
arXiv:2606.10388v4 Announce Type: replace-cross Abstract: A skill can match a task's topic while conflicting with its resource, procedure, or output requirements. We study this as same-capability risk-exposure retrieval…
- arXiv cs.AIresearchPretrained self-supervised speech models can recognize unseen consonants
arXiv:2606.11542v2 Announce Type: replace-cross Abstract: Modern pretrained self-supervised automatic speech recognition models are trained on large-scale audio data to encode speech into contextualized representations.…
- arXiv cs.AIresearchAnalyzing and Improving Fine-grained Preference Optimization in Medical LVLMs
arXiv:2606.12590v2 Announce Type: replace-cross Abstract: Preference optimization is increasingly used to post-train medical large vision-language models (LVLMs), yet it operates at a much coarser granularity than the on…
- arXiv cs.AIresearchLearned Image Compression for Vision-Language-Action Models
arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottleneck for real-time ro…
- arXiv cs.AIresearchPearlVLA: Progressive Embodied Action-Plan Refinement in Latent Space
arXiv:2606.17924v2 Announce Type: replace-cross Abstract: Current Vision-Language-Action (VLA) models face a trade-off between efficient action generation and explicit deliberation. Directly decoding actions from vision-…
- arXiv cs.AIresearchS4oP: Operator-level Pruning of Structured State Space Models for Resource-Constrained Devices
arXiv:2606.18096v2 Announce Type: replace-cross Abstract: Structured State Space Models (SSMs), including the S4 and S4D architectures, have recently emerged as powerful alternatives to attention-based models for capturi…
- arXiv cs.AIresearchLearning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards
arXiv:2606.18810v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative methods such as GRP…
- arXiv cs.AIresearchNeural Conjugate Aggregation: Identifiable Unsupervised Multi-Sensor Regression under Heterogeneous Sensor Bias
arXiv:2606.22200v2 Announce Type: replace-cross Abstract: We study regression-based data fusion under uncertainty, where multiple noisy and biased measurement sources are available but ground-truth labels are absent duri…
- arXiv cs.AIagentsThe Red Queen G\"odel Machine: Co-Evolving Agents and Their Evaluators
arXiv:2606.26294v3 Announce Type: replace-cross Abstract: Self-improving agents are state-of-the-art on agentic coding benchmarks, yet their search methods assume a stationary evaluation criterion. This ignores a central…