AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsScepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines
arXiv:2604.15186v3 Announce Type: replace-cross Abstract: Agentic workflows carry out complex tasks by orchestrating multiple large language models (LLMs) and tools. Serving them at a target throughput with low latency i…
- arXiv cs.AIagentsAn AI Agent Execution Environment to Safeguard User Data
arXiv:2604.19657v3 Announce Type: replace-cross Abstract: AI agents promise to serve as general-purpose personal assistants for their users, which requires them to have access to private user data (e.g., personal and fin…
- arXiv cs.AIagentsInformation Aggregation with AI Agents
arXiv:2604.20050v4 Announce Type: replace-cross Abstract: Can Large Language Models (AI agents) aggregate dispersed private information through trading and reason about the knowledge of others by observing price movement…
- arXiv cs.AIagentsVLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation
arXiv:2604.21375v3 Announce Type: replace-cross Abstract: Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without verifiable evidence, and repetitive loops,…
- arXiv cs.AIresearchHuman-1 by Josh Talks: A Full-Duplex Conversational Modeling Framework in Hindi using Real-World Conversations
arXiv:2604.23295v3 Announce Type: replace-cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems remain largely…
- arXiv cs.AIresearchTopology-Driven Anti-Entanglement Control for Soft Robots
arXiv:2605.05236v2 Announce Type: replace-cross Abstract: In the field of precision manufacturing in complex constrained environments, the role of soft robots is increasingly prominent, and the realization of anti-windin…
- arXiv cs.AIagentsStraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction
arXiv:2605.06642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon decision making remains difficult because current m…
- arXiv cs.AIresearchTransformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression
arXiv:2605.08475v3 Announce Type: replace-cross Abstract: In this paper, we study in-context kernel ridge regression (KRR) with Gaussian kernels and show, both theoretically and empirically, that a standard softmax-atten…
- arXiv cs.AIresearchCaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
arXiv:2605.11723v4 Announce Type: replace-cross Abstract: In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it first con…
- arXiv cs.AIresearchGrid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
arXiv:2605.12728v2 Announce Type: replace-cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more accessible analysi…
- arXiv cs.AIresearchAttention Sinks and Outliers in Attention Residuals
arXiv:2605.17887v2 Announce Type: replace-cross Abstract: We propose OASIS, an outlier- and sink-aware method that stabilizes dual-normalized attention-residual architectures through explicit null routing and token-to-de…
- arXiv cs.AIresearchRebalancing Reference Frame Dominance to Improve Motion in Image-to-Video Models
arXiv:2605.19398v5 Announce Type: replace-cross Abstract: Image-to-video models often generate videos that remain overly static, compared to text-to-video models. While prior approaches mitigate this issue by weakening o…
- arXiv cs.AIresearchSmooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions
arXiv:2605.19823v2 Announce Type: replace-cross Abstract: Neural operators have achieved strong performance in learning solution operators of partial differential equations (PDEs), but their inherently continuous represe…
- arXiv cs.AIresearchHide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
arXiv:2605.30834v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnerable to execu…
- arXiv cs.AIresearchINFUSER: Influence-Guided Self-Evolution Improves Reasoning
arXiv:2606.09052v5 Announce Type: replace-cross Abstract: Self-evolution offers a scalable path to stronger reasoning: a pretrained language model improves itself with only minimal external supervision. Yet existing meth…
- arXiv cs.AIresearchAttention-Discounted Adaptive Sampler for Masked Diffusion Language Models
arXiv:2606.10829v5 Announce Type: replace-cross Abstract: Masked diffusion language models can reduce inference steps by revealing multiple tokens per denoising iteration, but this parallelism is fragile: positions that…
- arXiv cs.AIresearchGenetic Algorithms with Optimization Guided Operators
arXiv:2606.12279v2 Announce Type: replace-cross Abstract: Recent work in ML applies genetic algorithms at inference time to iteratively improve solutions to optimization problems. The basic mutation and recombination ope…
- arXiv cs.AIresearchPolicy Regret for Embedding Model Routing: Contextual Bandits with Low-Rank Experts
arXiv:2606.14929v2 Announce Type: replace-cross Abstract: Modern recommendation systems increasingly rely on dynamically routing diverse queries to multiple embedding models. Despite its practical significance, this prob…
- arXiv cs.AIresearchEfficient Safety Benchmarking via Item Response Theory
arXiv:2606.20626v2 Announce Type: replace-cross Abstract: Safety benchmarks for language models are typically evaluated using static paradigms that treat all items as equally informative for all models, an assumption tha…
- arXiv cs.AIresearchBeyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark
arXiv:2606.30170v2 Announce Type: replace-cross Abstract: Generative molecular design is shaped by simple proxy benchmarks for drug-like properties and models pretrained on large pharmaceutical datasets. This combination…
- arXiv cs.AIresearchCoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation
arXiv:2607.02222v2 Announce Type: replace-cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decomposition, while the…
- arXiv cs.AIresearchWhen Do Cheap Probes Predict Expensive Training? Probing 3D-CT Encoders for Text Generation
arXiv:2607.22771v3 Announce Type: replace-cross Abstract: Building a 3D CT vision language model begins with a choice of which image encoder to build on. Today that choice is made by fine-tuning every candidate through t…
- arXiv cs.AIresearchBlind, Not Weak: A Best-of-Suite Safety-Utility Frontier for Recover-and-Reguard Defenses Against Encoded VLM Jailbreaks
arXiv:2607.26574v3 Announce Type: replace-cross Abstract: Safety classifiers ("guards") are the dominant black-box defense for vision-language models, yet a guard judges an input's surface form, not its meaning: a harmfu…
- arXiv cs.AIresearchDepth, Not Breadth: Best-of-N Jailbreaking Beyond Surface Noise
arXiv:2607.26639v3 Announce Type: replace-cross Abstract: Best-of-N jailbreaking spends a query budget on surface variation, scrambling and recasing a request until one draw lands. We ask what the same search buys when i…
- arXiv cs.AIagentsThink Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM Agents
arXiv:2607.26865v3 Announce Type: replace-cross Abstract: LLM agents following the ReAct paradigm are promising enablers of complex multi-step tasks, including multi-hop question answering, code generation, and control o…
- arXiv cs.AIresearchSmall Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters
arXiv:2607.29238v2 Announce Type: replace-cross Abstract: InMyStyle is a privacy-first, single-user system that adapts small language models to rewrite AI-edited text towards an individual user's writing style without an…
- arXiv cs.AIresearchNot Every Divergence Should Be Suppressed: Counterfactual Recoverability in On-Policy Distillation
arXiv:2608.04408v3 Announce Type: replace-cross Abstract: On-policy distillation (OPD) supervises student-visited trajectories, yet divergence-based rules cannot determine whether an erroneous prefix remains correctable.…
- arXiv cs.AIresearchDecoupling Intention from Trajectory: A Representational Deduction Framework for World Action Models
arXiv:2608.06994v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) aim to construct a unified architecture capable of understanding world state evolution and guiding to generative motion planning. Howev…
- arXiv cs.AIresearchTowards Unified Dynamic Face Landmark Detection
arXiv:2608.10346v2 Announce Type: replace-cross Abstract: Although advancements in face landmark detection (FLD) methods continue to push performance boundaries, they overlook two major functional limitations: (1) differ…
- arXiv cs.AIresearchBeyond Forecasting: Recasting Volatility Control as a Routing Problem
arXiv:2608.10375v2 Announce Type: replace-cross Abstract: Volatility control converts risk estimates into portfolio exposure, yet existing approaches often rely on a fixed volatility estimator or a pre-defined control ru…
- arXiv cs.AIresearchKeep the Future, Drop the Rollout: RIFT for World Action Models
arXiv:2608.11521v3 Announce Type: replace-cross Abstract: World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether action generatio…
- arXiv cs.AIresearchPolyChirp: Multi-Species Birdsong Classification Using TinyML on Low-Power Acoustic Sensors
arXiv:2608.23101v2 Announce Type: replace-cross Abstract: Recent progress in the field of TinyML has demonstrated that low-power hardware based on microcontrollers can achieve bird species monitoring in real time based o…
- arXiv cs.AIagentsSUN: Agentic Robot Policy Learning with Persistent Task Programs
arXiv:2608.31167v2 Announce Type: replace-cross Abstract: Model-based control can directly execute specified objectives, while learning can amortize such behaviors into reactive policies, making their combination a natur…
- arXiv cs.AIagentsProvably Safe Sim-to-Real Transfer
arXiv:2609.01418v2 Announce Type: replace-cross Abstract: We address safe sim-to-real transfer, in which an agent leverages an imperfect simulator and limited real-world interaction while ensuring safety throughout data…
- arXiv cs.AIresearchThe Geometry of Refusal: Why Post-Hoc Safety Is Fragile and Pretraining-Time Safety Persists
arXiv:2609.06934v2 Announce Type: replace-cross Abstract: Post-hoc safety training (RLHF, DPO) is the dominant way to align large language models, yet jailbreaks (Zou et al., 2023), fine-tuning attacks (Qi et al., 2024),…
- arXiv cs.AIresearchEGGROLL, Unrolled: Understanding and Improving Low-Rank Evolution Strategies at Scale
arXiv:2609.10980v2 Announce Type: replace-cross Abstract: EGGROLL (Sarkar et al., 2026) makes evolution strategies (ES) practical for LLMs by replacing dense Gaussian weight perturbations with low-rank Gaussian products,…
- arXiv cs.AIresearchExploring Second-Order Pattern Recognition in Speaker Recognition
arXiv:2609.11182v2 Announce Type: replace-cross Abstract: In traditional pattern recognition tasks, neural networks are trained to recognise human-defined patterns (e.g. audio categories) in model inputs (e.g. audio). Me…
- arXiv cs.AIresearchLarge Distant Gradients Need Not Be Reliable: reliability-weighted credit assignment for long-horizon autoregressive forecasting
arXiv:2609.12890v3 Announce Type: replace-cross Abstract: In autoregressive forecasting, long prediction rollouts provide distant supervision, but backpropagation through time (BPTT) carries gradients from those losses t…
- arXiv cs.AIresearchInterpreting hierarchical organisation of speaker embeddings
arXiv:2609.15203v2 Announce Type: replace-cross Abstract: Speaker recognition neural networks recognise speaker identities from input utterances by learning latent representations (i.e. speaker embeddings). However, thes…
- arXiv cs.AIresearchState of Thought Enables Endogenous Reasoning
arXiv:2609.16055v2 Announce Type: replace-cross Abstract: Test-time compute has emerged as a major approach to improving the capabilities of Large Language Models (LLMs). However, existing test-time reasoning paradigms r…
- arXiv cs.AIresearchProtoLIP: From Sentence-Level to Object-Level Evidence Disentanglement
arXiv:2609.16284v2 Announce Type: replace-cross Abstract: Query-conditioned vision-language models enable fine-grained interpretation by revealing which visual content supports a given textual query and how this evidence…
- Engadget AIsafetyHow to stop AI companies from training on your data
AI companies are able to improve their models by submitting users' conversations as training data. Opting out is easy, you just need to know where to look.
- LessWrongsafetyAI Futures: Racing to Lose, A sermon
This was given as a sermon on 2026-September-27 at https://kvuuc.net/ Time for all Ages: The story of the Three AIs Once upon a time, earlier this year, the company Anthropic was testing three Artificial Intelligences, o…
- LessWrongcommunityThe models have no plan, but we can fix that!
I posted a sloppier version of this essay with nearly identical semantic content earlier tonight, which you can read here . I've replaced that text with this one, which is less enthusiastic but more readable. I don't thi…
- SiliconANGLE AIagentsAWS CloudWatch Omni goes after the hardest question in agentic AI: Why did the agent do that?
For decades, the observability industry has answered one basic question: Is it running? Agentic artificial intelligence breaks that model. An agent can return a clean response, meet its latency target and throw no errors…
- Apple Machine Learning ResearchresearchFaster Rates for Federated Variational Inequalities
In this paper, we study federated optimization for solving stochastic variational inequalities (VIs), a problem that has attracted growing attention in recent years. Despite substantial progress, a significant gap remain…
- OpenAI NewscommunityAre you a Codex Original?
We’re collecting real stories of builders, tinkerers, researchers, and creators who are using Codex to do incredible things. If you want to be a part of the next chapter of the Codex Originals program, tell us more about…
- OpenAI NewsmodelsBasis completes a tax workbook 2x faster with GPT-6 Astra
GPT-6 Astra completed a 50-tab tax workbook twice as fast as GPT-5.6 Sol, and its stronger understanding of user intent gives Basis more confidence in real-world use.
- Hugging Face Blogopen-sourceWelcome RL Environments to the hub
Open-source model releases, tooling, and community updates.
- Simon Willison's Weblogmodels2026 in LLMs (so far)
On Friday I gave the closing keynote at the WeAreDevelopers World Congress North America in San Jose. I tied together the key trends from the past year into a chronological exploration of everything that happened in 2026…