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On the Sample Complexity of Learning for Blind Inverse Problems

arXiv:2512.23405v4 Announce Type: replace Abstract: Blind inverse problems arise in many experimental settings where both the signal of interest and the forward operator are (partially) unknown. In th

researcharxiv-cs-lg

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On the Shelf Life of Fine-Tuned LLM-Judges: Future-Proofing, Backward-Compatibility, and Question Generalization

DGX agent

arXiv:2509.23542v2 Announce Type: replace Abstract: The LLM-as-a-judge paradigm is widely used in both evaluating free-text model responses and reward modeling for model alignment and fine-tuning. Rec

safetyarxiv-cs-cl

21 Apr 2026

On the Theory of Continual Learning with Gradient Descent for Neural Networks

arXiv:2510.05573v2 Announce Type: replace-cross Abstract: Continual learning, the ability of a model to adapt to an ongoing sequence of tasks without forgetting earlier ones, is a central goal of arti

researcharxiv-cs-lg

One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment

arXiv:2601.18731v2 Announce Type: replace Abstract: Alignment of Large Language Models (LLMs) aims to align outputs with human preferences, and personalized alignment further adapts models to individu

safetyarxiv-cs-cl

one of my favorite quality of life features

one of my favorite quality of life features Claude Code in the terminal will now show recaps when you switch focus away from the session and then come back. This should help you stay more in flow whil

model-releasesthariq--x

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know…

researchfrancois-chollet--x

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know, how it knows, or how it could find out. It's a one-way sys

One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection

arXiv:2604.18393v1 Announce Type: new Abstract: Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under t

Agents

OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models

arXiv:2604.17915v1 Announce Type: new Abstract: Vision-Language Models(VLMs) excel at autoregressive text generation, yet end-to-end autonomous driving requires multi-task learning with structured out

agentsarxiv-cs-cv

Agents

OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

arXiv:2604.18486v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature

agentsarxiv-cs-cl

Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization

arXiv:2604.17984v1 Announce Type: new Abstract: Uncertainty quantification is crucial in safety-critical systems, where decisions must be made under uncertainty. In particular, we consider the problem

safetyarxiv-cs-lg

Only the fraud was stopped by DOGE and, even then, only some of the fraud

model-releaseselon-musk--x

Only the fraud was stopped by DOGE and, even then, only some of the fraud On Friday, @StateDeptGHSD released its first wave of PEPFAR data, covering July-Sept 2025, after State took over USAID’s lifes

ONTO: A Token-Efficient Columnar Notation for LLM Input Optimization

arXiv:2604.17512v1 Announce Type: new Abstract: Serialization formats designed for document interchange impose structural overhead that becomes prohibitive when large language models consume operation

researcharxiv-cs-cl

open-source community will work their magic!

open-source community will work their magic! If any inference providers could serve kimi k2.6 at 300+ tps reliably, I would be happy to switch from gpt 5.4 xhigh to kimi for daily tasks. It's a really

industryclem-delangue--x

Open-TQ-Metal: Fused Compressed-Domain Attention for Long-Context LLM Inference on Apple Silicon

arXiv:2604.16957v1 Announce Type: new Abstract: We present Open-TQ-Metal, the first implementation of fused compressed-domain attention on Apple Silicon, enabling 128K-context inference for Llama 3.1

Tutorials

OpenAI enables cost-per-click ads inside ChatGPT, setting bids at between 3 and 5 per click, in addition to CPMs (Digiday)

Digiday: OpenAI enables cost-per-click ads inside ChatGPT, setting bids at between 3 and 5 per click, in addition to CPMs — The platform that can figure out how to prove AI chatbots can drive an outco

tutorialstechmeme

OpenAI launches ChatGPT Images 2.0, Codex Labs developer training service

model-releasessiliconangle

OpenAI Group PBC today launched ChatGPT Images 2.0, an upgraded version of the image generator built into its popular chatbot. The company also debuted a new technical training service called Codex La

Tools

OpenAI's new Euphony tool works almost exactly the same way as my Codex transcript viewer https://tools.simonwillison.net/codex-timeline?url…

OpenAI's new Euphony tool works almost exactly the same way as my Codex transcript viewer https://tools.simonwillison.net/codex-timeline?url=https%3A%2F%2Fgist.githubusercontent.com%2Fsimonw%2Fa9eb599

toolssimon-willison--x

OpenAI’s updated image generator can now pull information from the web

OpenAI is rolling out the latest version of its AI-powered image generator with new 'thinking capabilities,' allowing it to search the web to help it create multiple images from a single prompt. On Tu

industrythe-verge-ai

OPeRA: A Dataset of Observation, Persona, Rationale, and Action for Evaluating LLMs on Human Online Shopping Behavior Simulation

model-releasesarxiv-cs-cl

arXiv:2506.05606v5 Announce Type: replace Abstract: Can large language models (LLMs) accurately simulate the next web action of a specific user? While LLMs have shown promising capabilities in generat

Operationalizing Fairness in Text-to-Image Models: A Survey of Bias, Fairness Audits and Mitigation Strategies

arXiv:2604.16516v1 Announce Type: new Abstract: Text-to-Image (T2I) generation models have been widely adopted across various industries, yet are criticized for frequently exhibiting societal stereoty

safetyarxiv-cs-cv

OPSDL: On-Policy Self-Distillation for Long-Context Language Models

arXiv:2604.17535v1 Announce Type: new Abstract: Extending the effective context length of large language models (LLMs) remains a central challenge for real-world applications. While recent post-traini

safetyarxiv-cs-cl

Optimal control of differentially flat underactuated planar robots in the perspective of oscillation mitigation

arXiv:2603.15528v2 Announce Type: replace Abstract: Underactuated robots are characterized by a larger number of degrees of freedom than actuators and if they are designed with a specific mass distrib

researcharxiv-cs-ro

Tutorials

Optimally Bridging Semantics and Data: Generative Semantic Communication via Schrodinger Bridge

arXiv:2604.17802v1 Announce Type: cross Abstract: Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-band and high-noise channels. However, existing GSC

tutorialsarxiv-cs-cv

OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives

model-releasesarxiv-cs-cv

arXiv:2604.17135v1 Announce Type: new Abstract: Offline vectorized maps constitute critical infrastructure for high-precision autonomous driving and mapping services. Existing approaches rely predomin

OptunaHub: A Platform for Black-Box Optimization

arXiv:2510.02798v2 Announce Type: replace Abstract: Black-box optimization (BBO) underpins advances in domains such as AutoML and Materials Informatics, yet implementations of algorithms and benchmark

Ordering with the Starbucks ChatGPT app was a true coffee nightmare

Venti iced coffee, light skim milk. That's what I get at Starbucks. It is what I have gotten at Starbucks every time I've been to Starbucks for as long as I can remember, other than a brief love affai

industrythe-verge-ai

ORSIFlow: Saliency-Guided Rectified Flow for Optical Remote Sensing Salient Object Detection

arXiv:2603.28584v2 Announce Type: replace Abstract: Optical Remote Sensing Image Salient Object Detection (ORSI-SOD) remains challenging due to complex backgrounds, low contrast, irregular object shap

Agents

Our core mission today is using AI to solve document OCR. All of our product offerings, from commercial (LlamaParse) to open-source (LitePar…

Our core mission today is using AI to solve document OCR. All of our product offerings, from commercial (LlamaParse) to open-source (LiteParse, ParseBench), are fully aligned towards solving this prob

agentsjerry-liu--x

Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Rendering

arXiv:2508.14461v3 Announce Type: replace Abstract: While multi-step diffusion models have advanced both forward and inverse rendering, existing approaches often treat these problems independently, le

Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference

arXiv:2604.18319v1 Announce Type: cross Abstract: Selection bias arises when the probability that an observation enters a dataset depends on variables related to the quantities of interest, leading to

OVOD-Agent: A Markov-Bandit Framework for Proactive Visual Reasoning and Self-Evolving Detection

arXiv:2511.21064v2 Announce Type: replace-cross Abstract: Open-Vocabulary Object Detection (OVOD) aims to enable detectors to generalize across categories by leveraging semantic information. Although

safetyarxiv-cs-cv

P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist

arXiv:2601.02986v2 Announce Type: replace Abstract: Recent approaches in personalized reward modeling have primarily focused on leveraging user interaction history to align model judgments with indivi

researcharxiv-cs-cl

PA-TCNet: Pathology-Aware Temporal Calibration with Physiology-Guided Target Refinement for Cross-Subject Motor Imagery EEG Decoding in Stroke Patients

arXiv:2604.16554v1 Announce Type: new Abstract: Stroke patient cross-subject electroencephalography (EEG) decoding of motor imagery (MI) brain-computer interface (BCI) is essential for motor rehabilit

PAC-Bayes Bounds for Gibbs Posteriors via Singular Learning Theory

arXiv:2604.17219v1 Announce Type: cross Abstract: We derive explicit non-asymptotic PAC-Bayes generalization bounds for Gibbs posteriors, that is, data-dependent distributions over model parameters ob

Parallel Test-Time Scaling for Latent Reasoning Models

model-releasesarxiv-cs-cl

arXiv:2510.07745v4 Announce Type: replace Abstract: Parallel test-time scaling (TTS) is a pivotal approach for enhancing large language models (LLMs), typically by sampling multiple token-based chains

Parkinson's Disease Detection via Self-Supervised Dual-Channel Cross-Attention on Bilateral Wrist-Worn IMU Signals

arXiv:2604.18372v1 Announce Type: new Abstract: Parkinson's disease (PD) is a chronic neurodegenerative disease. It shows multiple motor symptoms such as tremor, bradykinesia, postural instability, fr

researcharxiv-cs-lg

Applications

PARM: Pipeline-Adapted Reward Model

arXiv:2604.18327v1 Announce Type: cross Abstract: Reward models (RMs) are central to aligning large language models (LLMs) with human preferences, powering RLHF and advanced decoding strategies. While

applicationsarxiv-cs-cl

ParseBench is the first benchmark to include VLM chart understanding 📊📈📉 over enterprise documents. 🟠 Existing benchmarks (ChartQA, Char…

model-releasesjerry-liu--x

ParseBench is the first benchmark to include VLM chart understanding 📊📈📉 over enterprise documents. 🟠 Existing benchmarks (ChartQA, ChartXiv) test over charts specifically and not the chart's inclusio

PaTaRM: Bridging Pairwise and Pointwise Signals via Preference-Aware Task-Adaptive Reward Modeling

arXiv:2510.24235v3 Announce Type: replace Abstract: Reward models (RMs) are central to reinforcement learning from human feedback (RLHF), providing the critical supervision signals that align large la

safetyarxiv-cs-lg

Tutorials

Path-Based Quantum Meta-Learning for Adaptive Optimization of Reconfigurable Intelligent Surfaces

arXiv:2604.17690v1 Announce Type: cross Abstract: Reconfigurable intelligent surfaces (RISs) modify signal reflections to enhance wireless communication capabilities. Classical RIS phase optimization

tutorialsarxiv-cs-lg

PBSBench: A Multi-Level Vision-Language Framework and Benchmark for Hematopathology Whole Slide Image Interpretation

model-releasesarxiv-cs-cv

arXiv:2604.17570v1 Announce Type: new Abstract: Peripheral Blood Smear (PBS) is a critical microscopic examination in hematopathology that yields whole-slide imaging (WSI). Unlike solid tissue patholo

PCM-NeRF: Probabilistic Camera Modeling for Neural Radiance Fields under Pose Uncertainty

arXiv:2604.17831v1 Announce Type: new Abstract: Neural surface reconstruction methods typically treat camera poses as fixed values, assuming perfect accuracy from Structure-from-Motion (SfM) systems.

PDDL-Mind: Large Language Models are Capable on Belief Reasoning with Reliable State Tracking

model-releasesarxiv-cs-cl

arXiv:2604.17819v1 Announce Type: new Abstract: Large language models (LLMs) perform substantially below human level on existing theory-of-mind (ToM) benchmarks, even when augmented with chain-of-thou

Pearmut: Human Evaluation of Translation Made Trivial

arXiv:2601.02933v3 Announce Type: replace Abstract: Human evaluation is the gold standard for multilingual NLP, but is often skipped in practice and substituted with automatic metrics because it is no

researcharxiv-cs-cl

Peerispect: Claim Verification in Scientific Peer Reviews

arXiv:2604.17667v1 Announce Type: new Abstract: Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitt

safetyarxiv-cs-cl

Penny Wise, Pixel Foolish: Bypassing Price Constraints in Multimodal Agents via Visual Adversarial Perturbations

model-releasesarxiv-cs-cv

arXiv:2604.16515v1 Announce Type: new Abstract: The rapid proliferation of Multimodal Large Language Models (MLLMs) has enabled mobile agents to execute high-stakes financial transactions, but their a

Pentagon pulls the plug on one of the military's most troubled space programs

The Space Force cancelled the Next Generation Operational Control System (OCX) contract, a troubled GPS ground control system program under prime contractor RTX , after spending $6.27 billion as of Ja

industryars-technica

Pentagon wants $54B for drones, more than most nations’ military budgets

The Pentagon's 1.5 trillion fiscal 2027 budget proposal allocates nearly 54 billion for military drones and related technology, plus 21 billion for counter-drone weapons systems. At nearly 54 billion,

industryars-technica