AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchGefen: Optimized Stochastic Optimizer
arXiv:2606.13894v4 Announce Type: replace-cross Abstract: AdamW is a default optimizer for deep learning, but its moment states add two parameter-sized buffers to training memory, increasing the cost of large-scale pretr…
- arXiv cs.AIresearchMachine learning modeling of hit-into-play probability and quantification of pitch sequence effects
arXiv:2606.17345v2 Announce Type: replace-cross Abstract: Although pitch sequencing is a central topic in baseball analytics, previous studies have primarily focused on improving predictive performance for the final pitc…
- arXiv cs.AIresearchEG-VQA: Benchmarking Verifiable Video Question Answering with Grounded Temporal Evidence
arXiv:2606.24797v2 Announce Type: replace-cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have yielded promising performance on Video Question Answering (VideoQA). Nevertheless, existing bench…
- arXiv cs.AIresearchNarrative-UFET: Narrative Generation for Ultra-Fine Entity Typing
arXiv:2606.27598v2 Announce Type: replace-cross Abstract: Ultra-fine entity typing (UFET) assigns highly specific types to entity mentions, but current approaches struggle with types in the long tail. We hypothesize that…
- arXiv cs.AIresearchBehavior Uncloning: Distilling Mode Redirection into Policy Weights without Inference-Time Steering
arXiv:2606.29201v3 Announce Type: replace-cross Abstract: Behavior-cloned policies often learn multiple behavior modes from demonstration datasets, including modes that are unsafe or otherwise undesired at deployment. Fo…
- arXiv cs.AIresearchMulti-Level Distributional Entropy from Flow Summary Statistics for Explainable Network Intrusion Detection
arXiv:2606.29797v2 Announce Type: replace-cross Abstract: Machine learning network intrusion detection systems (IDS) operate on aggregate flow statistics that discard the distributional structure of traffic, and although…
- arXiv cs.AIresearchAnchored or Drifting: What Recursive Self-Generation Reveals About Training Data
arXiv:2606.31991v2 Announce Type: replace-cross Abstract: Large generative models are known to memorize their training data, posing severe privacy risks. Yet, current methods to detect training membership typically rely…
- arXiv cs.AIagentsEgoSafetyBench: A Diagnostic Egocentric Video Benchmark for Evaluating Embodied VLMs as Runtime Safety Guards
arXiv:2607.00218v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) are increasingly proposed as runtime safety guards for embodied agents in homes and factories. A deployable guard must catch genuine…
- arXiv cs.AIresearchMeta-Transfer Learning for mmWave Beam Alignment
arXiv:2607.00860v2 Announce Type: replace-cross Abstract: Millimeter-wave (mmWave) beam alignment is critical for next-generation wireless systems, but existing approaches either update all parameters during adaptation o…
- arXiv cs.AIagentsFrom Personas to Plot: Character-Grounded Multi-Agent Story Generation for Long-Form Narratives
arXiv:2607.00918v2 Announce Type: replace-cross Abstract: Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and coherent plot…
- arXiv cs.AIresearchOffice Comprehension Benchmark
arXiv:2607.01245v2 Announce Type: replace-cross Abstract: We introduce Office Comprehension Bench (OCB), the first public benchmark to jointly evaluate LLM systems on Word, Excel, and PowerPoint comprehension over native…
- arXiv cs.AIresearchAnyGroundBench: A Multi-Domain Adaptation Benchmark for Video Grounding in VLMs
arXiv:2607.02269v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have shown strong performance in Spatio-Temporal Video Grounding (STVG), yet they are still evaluated mostly in a zero-shot manner o…
- arXiv cs.AIresearchSafe Inference-Time Alignment via Lagrangian Reward Augmentation
arXiv:2607.02781v2 Announce Type: replace-cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates. However, exi…
- arXiv cs.AIresearchMask2Real-WM: Controllable Dexterous World Models via Segmentation Masks as a Sim-to-Real Bridge
arXiv:2607.04546v3 Announce Type: replace-cross Abstract: Learning action-conditioned world models for dexterous manipulation that are genuinely controllable requires capturing complex, high-dimensional hand kinematics f…
- arXiv cs.AIresearchUI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation
arXiv:2607.06306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated growing competence in generating web pages from UI screenshots, which convey both visual structure and cues to appl…
- arXiv cs.AIresearchCo-LMLM: Continuous-Query Limited Memory Language Models
arXiv:2607.07707v2 Announce Type: replace-cross Abstract: Externalizing knowledge in LLM pre-training is a promising avenue to achieve higher performance at smaller scales, control knowledge use, and overall increase mod…
- arXiv cs.AIresearchAuthority-Bound Governance of Heterogeneous AI Security Decisions in Telecom and IoT Networks
arXiv:2607.09259v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI)-enabled security decision systems in telecom and IoT networks can draw on heterogeneous models whose outputs may trigger operational…
- arXiv cs.AIresearchExact and Certified Data Shapley for Weighted Nearest Neighbor Regression
arXiv:2607.11956v3 Announce Type: replace-cross Abstract: Data Shapley can be computed exactly and efficiently for unweighted K-nearest-neighbor (KNN) models, the basis of the popular KNN-Shapley. For weighted KNN, howev…
- arXiv cs.AIagentsPFAdapter: Hierarchical LoRA Decomposition for Personalized Federated MLLMs
arXiv:2607.12111v2 Announce Type: replace-cross Abstract: Agentic AI systems are reshaping communications and networking by deploying autonomous intelligent agents capable of collaborative learning while maintaining data…
- arXiv cs.AIresearchContinual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning
arXiv:2607.12112v2 Announce Type: replace-cross Abstract: Federated fine-tuning of Multimodal Large Language Models (MLLMs) across distributed networks enables privacy-sensitive adaptation to evolving data streams, yet a…
- arXiv cs.AIagentsMemory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents
arXiv:2607.13591v3 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from gra…
- arXiv cs.AIresearchCAS I: A Geometric Coding Theorem
arXiv:2607.13796v2 Announce Type: replace-cross Abstract: This paper establishes a direct analogue of the classical Coding Theorem in the setting of symmetry groups. We consider computable bijections on the set of binary…
- arXiv cs.AIresearchSLPO: Scaling Latent Reasoning via a Surrogate Policy
arXiv:2607.19691v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards has become the predominant recipe for eliciting test-time scaling in explicit Chain-of-Thought reasoners. Yet this…
- arXiv cs.AIresearchMedical foundation models converge less under label supervision
arXiv:2607.20274v3 Announce Type: replace-cross Abstract: Diagnostic classifiers and imaging biomarkers are fitted on the embeddings of medical foundation models. These models are replaced as new versions appear. This pr…
- arXiv cs.AIagentsLooping Is Not Reliability: State-Bound Evidence and Typed Revision Contracts for Agentic Code Repair
arXiv:2607.24604v3 Announce Type: replace-cross Abstract: Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee. We study the gap between finding a correct patch…
- arXiv cs.AIresearchWhen Synthetic Users Fail: A Cross-Domain Benchmark of LLM-Simulated Human Survey Responses
arXiv:2607.26348v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market de…
- arXiv cs.AIagentsThe Implementation Lottery: Auditing Idea Reliability in Automated Research
arXiv:2607.26587v2 Announce Type: replace-cross Abstract: Automated research agents use program scores to judge ideas. We call variation in this evidence across implementations the implementation lottery. We introduce an…
- arXiv cs.AIresearchCost-Effective Automated Judging of Natural-Language Mathematical Proofs
arXiv:2608.00004v2 Announce Type: replace-cross Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whether cheap…
- arXiv cs.AIresearchTraining nGPT
arXiv:2608.01284v3 Announce Type: replace-cross Abstract: The normalized Transformer (nGPT) realizes hyperspherical representation learning by constraining model parameter vectors and activation vectors to the unit hyper…
- arXiv cs.AIagentsMemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale
arXiv:2608.02613v2 Announce Type: replace-cross Abstract: Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models. Yet, existing memory benchmarks often…
- arXiv cs.AIresearchCLEARMIND: Closed-Form Laplacian Embeddings of Arakelov-Green Resistance for Morphological Intrinsic Neuronal Distances
arXiv:2608.04460v2 Announce Type: replace-cross Abstract: Tropical geometry turns a metric graph into a flat torus, its tropical Jacobian, and measures distances between the images of its points by a closest vector probl…
- arXiv cs.AIresearchSite Is Decodable Before Pretraining: Negative Controls for Probing Frozen Brain-MRI Foundation Models
arXiv:2608.10295v2 Announce Type: replace-cross Abstract: Brain foundation models are often tested with a probe. The model is frozen, a simple classifier is trained on its output, and the classifier's accuracy is taken a…
- arXiv cs.AIresearchThe AI Accountability Ecosystem in the Era of Language Models
arXiv:2608.12320v2 Announce Type: replace-cross Abstract: This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the latest devel…
- arXiv cs.AIresearchLearn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
arXiv:2608.16072v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training language model reasoners. However, when optimizing m…
- arXiv cs.AIresearchThe Acknowledgment Point Is the System: Durable Policy-Decision Receipts for AI Audit Evidence
arXiv:2608.17176v2 Announce Type: replace-cross Abstract: An AI audit record is useful only if its durability and trust boundary are explicit. Returning a guarded decision before any durable write minimizes latency, but…
- arXiv cs.AIagentsScience Done on a Machine by a Machine: AI Agents in Computational Chemistry
arXiv:2608.18508v2 Announce Type: replace-cross Abstract: We are witnessing an explosion of agentic systems for computational chemistry: from four in 2024 to seventeen in 2025 and over sixty now, surveyed here. What is d…
- arXiv cs.AIresearchTRACE: Training-time Report-guided and Clinically Ordered Concept Editing
arXiv:2608.20809v2 Announce Type: replace-cross Abstract: Breast ultrasound diagnosis relies on clinically meaningful semantic concepts, yet most deep learning methods adopt end-to-end image-to-label paradigms that lack…
- arXiv cs.AIresearchDoes Fine-Tuning Undo Activation Steering? Behavioural Recovery Without Weight-Edit Reversal
arXiv:2608.24988v2 Announce Type: replace-cross Abstract: Activation steering can be embedded directly into a language model's weights, shaping behaviour without inference-time intervention and offering a way to encode a…
- arXiv cs.AIresearchPointing the Way, Hiding the Destination: Practical Private Dense Retrieval at Scale
arXiv:2608.25735v2 Announce Type: replace-cross Abstract: Hosted retrieval-augmented generation (RAG) and semantic search allow users to query valuable provider-held corpora, raising two competing demands: to hide each q…
- arXiv cs.AIresearchDifference-in-Differences on a Censored Rating Scale Can Manufacture an Effect: Evidence from a Pre-Registered LLM-Judge Audit
arXiv:2608.27309v5 Announce Type: replace-cross Abstract: LLM-judge audits assess bias by comparing ratings across matched conditions. Difference-in-differences designs take the rating difference between two candidate re…
- arXiv cs.AIresearchThe Hallucination Signal Is a Mean Shift: Why Simple Probes Suffice
arXiv:2608.28930v2 Announce Type: replace-cross Abstract: Hidden-state probes effectively detect LLM hallucinations, but the geometry of the signal remains poorly characterized, driving increasingly complex probe archite…
- arXiv cs.AIresearchCPR for LLMs: Critical-Point Routing against Catastrophic Forgetting in Domain Adaptation
arXiv:2608.30158v4 Announce Type: replace-cross Abstract: Supervised fine-tuning (SFT) is the de facto standard for adapting large language models (LLMs) to target domains, but it often degrades the model's general capab…
- arXiv cs.AIagentsSIR: Self-improving Red-teaming for Compute Use Agents
arXiv:2608.30207v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) are agents powered by vision-language models (VLMs) that perceive a screen and operate an operating system through mouse, keyboard, and…
- arXiv cs.AIresearchCapability-Gated Language Models: Security Composes, Utility Does Not
arXiv:2609.00445v3 Announce Type: replace-cross Abstract: Deployed language model safeguards (safety fine-tuning, filtering, unlearning) vary by principal only outside the model weights: filters are reconfigured, tiers a…
- arXiv cs.AIagentsFrom Fixed Keys to Readable Schemas: Small Language Models for Vehicle Agent Function Calls
arXiv:2609.09476v2 Announce Type: replace-cross Abstract: In-vehicle assistants must translate natural-language requests into accurate vehicle function calls under strict memory and latency constraints, making small lang…
- arXiv cs.AIresearchA Measured Communication-Quality Frontier for Federated LoRA Fine-Tuning with Adaptive Phase-Switching
arXiv:2609.13512v2 Announce Type: replace-cross Abstract: Federated fine-tuning of large language models with low-rank adaptation (LoRA) reduces the number of trainable parameters, but communication remains the dominant…
- arXiv cs.AIresearchTriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps
arXiv:2609.14762v2 Announce Type: replace-cross Abstract: Operational logs create a need for private, resource-efficient incident analysis, but aggregate detection scores can conceal severe prediction bias. We present Tr…
- SiliconANGLE AIpolicyUtah gives startup Nolla Health permission to start issuing AI automated prescriptions for acne treatments
Utah has become the first state in the U.S. to give an artificial intelligence startup permission to automate the approval of prescription refills with only minimal oversight from human physicians. In a blog post today,…
- LessWrongresearchTakes One to Know One - Training a model to grade reward hacks causes it to reward hack less itself
Code The question I asked in this project was - if I finetune a model to judge/catch reward hacks, does it change its behavior when completing the tests itself. Does it learn to hack more or less? Why it’s worth pursuing…
- LessWrongresearchYou can graft SDF changes from base models onto post-trained models
Webpage: praxis-research.org/grafting | Paper link: https://arxiv.org/abs/2610.00767 Work done during Peter and Dani's MATS Fellowship (10.0) under the mentorship of Shi, with Jinghua Ou as Research Manager. TLDR; We sha…