AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchForeground-Aware Dataset Distillation via Dual-Path Patch Selection
arXiv:2601.02727v2 Announce Type: replace-cross Abstract: In this paper, we propose a foreground-aware dataset distillation method that performs content-adaptive dual-path patch selection. With the rising computational c…
- arXiv cs.AIresearchThe Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AI
arXiv:2601.03222v4 Announce Type: replace-cross Abstract: As conversational AI systems become a larger part of the media landscape, they raise questions about whose interests they serve and the risks they may pose to use…
- arXiv cs.AIresearchBeyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Versatile Image Generation
arXiv:2601.12401v4 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has emerged as a paradigm for fine-tuning large-scale generative models, such as diffusion and flow models, to align with complex huma…
- arXiv cs.AIresearchSQuID: A Benchmark for Quantitative Spatial Reasoning on Satellite Imagery
arXiv:2601.13401v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) describe satellite images fluently but struggle with the quantitative spatial reasoning that remote sensing (RS) analysts perform ro…
- arXiv cs.AIresearchA swap-adversarial framework for domain generalization in pre- and post-stimulation Parkinsonian state classification
arXiv:2602.10528v3 Announce Type: replace-cross Abstract: We propose a novel swap-adversarial framework that mitigates high inter-subject variability and the high-dimensional low-sample-size problem in electrocorticograp…
- arXiv cs.AIresearchMIDAS: Mosaic Input-Specific Differentiable Architecture Search
arXiv:2602.17700v2 Announce Type: replace-cross Abstract: Differentiable Neural Architecture Search (NAS) provides efficient, gradient-based methods for automatically designing neural networks, yet its adoption remains l…
- arXiv cs.AIagentsAgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purification
arXiv:2602.22724v2 Announce Type: replace-cross Abstract: Tool-augmented large language model (LLM) agents aggregate dialogue history, tool outputs, and retrieved content into an accumulated runtime state to complete mul…
- arXiv cs.AIresearchPreconditioned Flow Matching
arXiv:2603.02337v3 Announce Type: replace-cross Abstract: Flow matching (FM) learns vector fields by regressing stochastic velocity targets along intermediate distributions $p_t$. We identify a geometric optimization bot…
- arXiv cs.AIagentsSWE-Skills-Bench: Do Agent Skills Actually Help in Real-World Software Engineering?
arXiv:2603.15401v2 Announce Type: replace-cross Abstract: Agent skills, structured procedural knowledge packages injected at inference time, are increasingly used to augment LLM agents on software engineering tasks. Howe…
- arXiv cs.AIresearchA Computationally Efficient Multi-Section Whole Slide Image Analysis for Capturing Prostate Cancer Multifocality in Biochemical Recurrence Prediction
arXiv:2603.20273v2 Announce Type: replace-cross Abstract: Prostate cancer is among the most frequently diagnosed malignancies in men worldwide. However, precise prediction of biochemical recurrence (BCR) after radical pr…
- arXiv cs.AIresearchCtrl-A: Control-Driven Machine Learning using Adaptive Online Data Augmentation
arXiv:2603.21819v2 Announce Type: replace-cross Abstract: We introduce ControlAugment (Ctrl-A), an automated data augmentation algorithm for image-vision tasks, which incorporates principles from control theory for onlin…
- arXiv cs.AIresearchSemLoc: Structured Grounding of Free-Form LLM Reasoning for Fault Localization
arXiv:2603.29109v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can describe what a piece of code should compute, but they do so in free-form text. Such text cannot be checked against program execu…
- arXiv cs.AIresearchScoring-Rule Sensitivity in LLM Evaluation: Evidence from Indian Financial Regulatory Text
arXiv:2604.19298v3 Announce Type: replace-cross Abstract: A benchmark leaderboard reports one accuracy number, but that number is a joint product of a model and a scoring rule. We ask what changes when only the rule chan…
- arXiv cs.AIresearchAmaraSpatial-10K: A Spatially and Semantically Aligned 3D Dataset for Spatial Computing and Embodied AI
arXiv:2604.23018v3 Announce Type: replace-cross Abstract: Web-scale 3D asset collections are abundant but rarely ready to ingest without cleanup, suffering from arbitrary metric scaling, incorrect pivots, brittle geometr…
- arXiv cs.AIresearchDeGenTWeb: A First Look at MGT-dominant Websites
arXiv:2605.00087v2 Announce Type: replace-cross Abstract: Many news reports have claimed that machine-generated text (MGT) from large language models (LLMs) is taking over the web. However, these claims are typically not…
- arXiv cs.AIresearchOn the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization
arXiv:2605.02141v2 Announce Type: replace-cross Abstract: Kullback-Leibler (KL) regularization is widely used in offline decision-making and offers several benefits, motivating recent work on the sample complexity of off…
- arXiv cs.AIresearchPosterior-First Neural PDE Simulation: Inferring What Downstream Tasks Need from a Single Field
arXiv:2605.03247v2 Announce Type: replace-cross Abstract: Neural PDE simulators often receive only a single observed field at deployment. In this setting, a field-to-future predictor can collapse distinct latent problem…
- arXiv cs.AIresearchDr. Post-Training: A Data Regularization Perspective on LLM Post-Training
arXiv:2605.07063v2 Announce Type: replace-cross Abstract: Data selection methods address a critical challenge in LLM post-training: effectively leveraging scarce, high-fidelity target data alongside abundant but imperfec…
- arXiv cs.AIresearchOn the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems
arXiv:2605.07860v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT) environment…
- arXiv cs.AIresearchRePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models
arXiv:2605.09410v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models remain brittle in long-horizon, contact-rich manipulation because success-only imitation provides little supervision for execu…
- arXiv cs.AIresearchThe Geometry of Learning: Read-Write Asymmetry Across Training
arXiv:2605.16600v2 Announce Type: replace-cross Abstract: Pretraining and alignment update the same transformer weights, and we ask in which directions each stage changes them. The residual stream gives every matrix a sh…
- arXiv cs.AIresearchBoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
arXiv:2605.17000v2 Announce Type: replace-cross Abstract: Optimization of LLM training and inference configurations, such as hyperparameters, data mixtures, and prompts, is critical to performance, but it is often approa…
- arXiv cs.AIresearchLLM Code Smells: A Taxonomy and Detection Approach
arXiv:2605.22976v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly integrated into software systems for diverse purposes, due to their versatility, flexibility, and ability to simulat…
- arXiv cs.AIresearchHidden-State Privacy Has an Empty Middle
arXiv:2605.24042v4 Announce Type: replace-cross Abstract: Of $1{,}536$ Gaussian release covariances we tested for single-layer hidden-state privacy, zero achieve both moderate utility and moderate privacy against an adap…
- arXiv cs.AIagentsDoes The Way You Plan Matter? An Empirical Study of Planning Representations for LLM Web Agents
arXiv:2605.29927v2 Announce Type: replace-cross Abstract: Despite recent advances, LLM-based web agents still struggle with limited exploration, omission of critical steps, and sensitivity to task constraints. Prior work…
- arXiv cs.AIresearchCalArena: A Large-Scale Post-Hoc Calibration Benchmark
arXiv:2605.30188v3 Announce Type: replace-cross Abstract: Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibration provid…
- arXiv cs.AIresearchGrasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation
arXiv:2606.03385v2 Announce Type: replace-cross Abstract: In robotic manipulation, the tight coupling between grasping and motion planning often obscures the true source of failure, leading to inefficient trial-and-error…
- arXiv cs.AIagentsStreaming Communication in Multi-Agent Reasoning
arXiv:2606.05158v3 Announce Type: replace-cross Abstract: Multi-agent reasoning systems adopt a generate-then-transfer paradigm that forces end-to-end latency to scale linearly with pipeline depth. We introduce StreamMA,…
- arXiv cs.AIresearchDRIFT: A Residual Flow Adapter for Decoding Continuous Outputs in Vision-Language Models
arXiv:2606.05758v2 Announce Type: replace-cross Abstract: Many modern vision-language models (VLMs) build on autoregressive decoding of discrete tokens. While text-based output interfaces enable scalable pretraining and…
- arXiv cs.AIresearchLLMs Can Leak Training Data But Do They Want To? Evaluating Memorization Propensity in LLMs
arXiv:2606.06286v2 Announce Type: replace-cross Abstract: Large language models can reproduce training data, but memorization evaluations mostly measure whether models can be made to do so, not whether they do so without…
- arXiv cs.AIresearchWhat Makes Video World Model Latents Action-Relevant: Prediction over Reconstruction
arXiv:2606.07687v2 Announce Type: replace-cross Abstract: Video world models are increasingly used to provide predictive visual representations, yet it remains unclear which pretraining signals induce action-relevant str…
- arXiv cs.AIresearchSpatio-Temporal Audio Language Modeling for Dynamic Sound Sources
arXiv:2606.14141v2 Announce Type: replace-cross Abstract: Sound events have semantic identities, locations, and trajectories, yet existing audio-language models typically encode clips as global event content. Conversely,…
- arXiv cs.AIresearchDifFRACT: Diffusion Feature Reconstruction and Attribution for Circuit Tracing
arXiv:2606.15796v2 Announce Type: replace-cross Abstract: While transcoder-based circuit tracing has recently enabled detailed causal analyses of large language models, it remains unclear how semantic information propaga…
- arXiv cs.AIresearchLineageMark: Multi-user White-box Watermarking for Contribution Tracing in Model Derivation Chains
arXiv:2606.17123v2 Announce Type: replace-cross Abstract: In open large language model (LLM) ecosystems, models are frequently adapted across multiple domains and applications, forming multi-stage derivation chains. Cons…
- arXiv cs.AIresearchTokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems
arXiv:2606.25147v2 Announce Type: replace-cross Abstract: User modeling in industrial recommender systems typically produces dense embeddings, which suffer from representational constraints due to fixed-dimensional vecto…
- arXiv cs.AIresearchTrust Region Policy Distillation
arXiv:2607.04751v2 Announce Type: replace-cross Abstract: Big goals are hard to achieve all at once; breaking them into small steps is wiser. We present Trust Region Policy Distillation (TOP-D), which transforms the noto…
- arXiv cs.AIresearchFrom Language to Navigation Goals: A Vision-Language Approach for Semantic Navigation of Mobile Robots Using RGB-D Perception
arXiv:2607.13624v2 Announce Type: replace-cross Abstract: Natural language interaction provides an intuitive way for non-expert users to communicate with robotic platforms. However, transforming user requests into execut…
- arXiv cs.AIresearchFrom Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
arXiv:2607.25687v2 Announce Type: replace-cross Abstract: Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the complex inter…
- arXiv cs.AIresearchTextCloak: Safeguarding Data from Unauthorized LLM Fine-Tuning via RL-Driven Unlearnable Examples
arXiv:2607.28862v2 Announce Type: replace-cross Abstract: The development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concer…
- arXiv cs.AIresearchActionable CBFI: Prescriptive Interventional Diagnosis and Interaction-Aware Escalation for Sparse Causal Algorithmic Recourse
arXiv:2608.27821v3 Announce Type: replace-cross Abstract: Algorithmic recourse tells an individual which feasible actions would change an unfavourable prediction. Feature attribution explains a prediction, but the most i…
- arXiv cs.AIresearchFrom Perspective to Fisheye Depth Estimation and Open-Vocabulary Segmentation
arXiv:2608.27860v2 Announce Type: replace-cross Abstract: Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be attributed to t…
- arXiv cs.AIresearchCan LLMs Design Video Coding Tools? A Case Study on Planar Mode
arXiv:2609.01535v2 Announce Type: replace-cross Abstract: This paper explores whether large language models (LLMs) can design video coding tools, a highly challenging task due to the intricate algorithmic coupling of too…
- arXiv cs.AIresearchMUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesis
arXiv:2609.17169v2 Announce Type: replace-cross Abstract: Forecasting anatomical changes such as tumor growth and neurodegeneration is a challenging generative vision task. Morphological evolution is subtle relative to s…
- LessWrongcommunityGreat but Painful
If you want to build a product that people will use, find something that people already do and make it less painful. People are notoriously bad at knowing what they want. If you ask someone what they want then they will…
- LessWrongcommunityWhen I Salsa dance, am I supposed to... try?
I had my birthday party on a Saturday in August. After the party ended, a few of us went out to a nearby bar. Most of my family on my mom’s side is Ecuadorian [1] , and my cousin from that side of the family was with us.…
- The Verge AIcommunityVoters in Texas agree: They hate data centers
Ask Texas NAACP president Gary Bledsoe what it's been like to see data center developers descend upon Austin and its surrounding suburbs and he can rattle off project after project facing opposition from locals. There's…
- TechRadar AImodelsMoscow could design an F-22 rival using an AI model from Russia's JPMorgan Chase — Sberbank GigaChat used its LLM for a 'generative design of a new aircraft'
Mainstream AI news from a large tech publication.
- The Register AI + MLmodelsAI slows growth for Infosys and keeps it afloat at the same time
Predicts slower growth as savings from automation hit price of extended deals
- LessWrongcommunityI spent 12 hours writing an article for LessWrong, calling for a more ‘hippie’ rationalism. Then I didn’t post it. This is why (plus a link to the article, explicitly not located on LessWrong)
TLDR I (and many others in the community) wish to see the universe unfold to its highest potential in the metaphorical palm of an AI as aligned as the most benevolent Buddhist monk – but I (we) feel the community's ontol…
- LessWrongresearchQuantum Mechanics Overview
[LW meta: This is a very brief overview of what quantum mechanics says and how it relates to ordinary reality. Many readers here will probably already be familiar with this material, especially if they've read Eliezer's…