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One trend that I think you might start to see at big companies is insourcing via hiring: why pay so many outside vendors (legal, marketing, …

applicationsethan-mollick--x

One trend that I think you might start to see at big companies is insourcing via hiring: why pay so many outside vendors (legal, marketing, software vendors) when you can hire in-house and harness AI

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Tutorials

Online Algorithms with Unreliable Guidance

DGX agent

arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p

tutorialsarxiv-cs-ai

19 May 2026

Online Conformal Prediction for Non-Exchangeable Panel Data

arXiv:2605.17705v1 Announce Type: cross Abstract: Panel data, in which multiple units are repeatedly observed over time, arise throughout science and engineering. Quantifying predictive uncertainty in

Online Learnability of Chain-of-Thought Verifiers: Soundness and Completeness Trade-offs

arXiv:2603.03538v3 Announce Type: replace Abstract: Large Language Models (LLMs) with chain-of-thought generation have demonstrated great potential for solving complex reasoning and planning tasks. Ho

safetyarxiv-cs-lg

Online Resource Allocation with Convex-set Machine-Learned Advice

arXiv:2306.12282v2 Announce Type: replace-cross Abstract: Decision-makers often have access to machine-learned predictions about future demand that can help guide online resource allocation decisions.

Open Set Face Forgery Detection via Dual-Level Evidence Collection

arXiv:2512.04331v2 Announce Type: replace Abstract: The surge in face forgeries has increasingly undermined confidence in the authenticity of online content. As generation algorithms rapidly evolve, n

applicationsarxiv-cs-cv

open sourcing Marlin-2B 🐟 a tiny VLM to extract structured information from videos Marlin is finetuned for two questions devs want to ask i…

model-releasesclem-delangue--x

open sourcing Marlin-2B 🐟 a tiny VLM to extract structured information from videos Marlin is finetuned for two questions devs want to ask in their videos: what is happening, and when? Best open model

Industry

OpenAI introduces Guaranteed Capacity, a new offering that lets customers guarantee access to OpenAI's compute through one- to three-year commitments (OpenAI)

OpenAI: OpenAI introduces Guaranteed Capacity, a new offering that lets customers guarantee access to OpenAI's compute through one- to three-year commitments — Guarantee long-term access to OpenAI com

industrytechmeme

OpenAI's win against Elon Musk leaves it free to continue its IPO plans, but it still faces many issues, like rising competition and dozens of other lawsuits (New York Times)

New York Times: OpenAI's win against Elon Musk leaves it free to continue its IPO plans, but it still faces many issues, like rising competition and dozens of other lawsuits — A jury's rejection of El

applicationstechmeme

OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention

arXiv:2605.06088v2 Announce Type: replace Abstract: Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semanti

OpenJarvis: Personal AI, On Personal Devices

arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local

OPERA: A Reinforcement Learning--Enhanced Orchestrated Planner-Executor Architecture for Reasoning-Oriented Multi-Hop Retrieval

arXiv:2508.16438v4 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) and dense retrievers have driven significant progress in retrieval-augmented generation (RAG).

Agents

OProver: A Unified Framework for Agentic Formal Theorem Proving

arXiv:2605.17283v1 Announce Type: cross Abstract: Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely i

agentsarxiv-cs-ai

Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach

arXiv:2307.12405v2 Announce Type: replace Abstract: We propose a machine learning approach to the optimal control of multiclass fluid queueing networks (MFQNETs) that provides explicit and insightful

safetyarxiv-cs-lg

Optimal Knock-Pick Planning for Tightly Packed Tabletop Blocks With Parallel Grippers

arXiv:2605.17800v1 Announce Type: cross Abstract: Rearranging densely packed tabletop objects is challenging when parallel-gripper picks are infeasible without sufficient clearance around an object. T

researcharxiv-cs-ai

Optimising CSRNet with parameter-free attention mechanisms for crowd counting in public transport

arXiv:2605.18349v1 Announce Type: cross Abstract: Occupancy estimation and crowd counting are critical tasks in designing smart and efficient public transport vehicles. Given that public transport loa

OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation

arXiv:2605.17197v1 Announce Type: cross Abstract: Post-disaster damage assessment requires rapid and accurate semantic segmentation of 3D point clouds to identify critical infrastructure such as damag

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

arXiv:2605.16363v1 Announce Type: new Abstract: Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective

OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence

arXiv:2605.16395v1 Announce Type: cross Abstract: We present OrbiSim, a novel robotic simulation paradigm that redefines world models as a fully differentiable physics engine for embodied intelligence

safetyarxiv-cs-lg

Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels

arXiv:2509.02351v3 Announce Type: replace-cross Abstract: Labeled data is a fundamental component in training supervised deep learning models for computer vision tasks. However, the labeling process,

Agents

ORION: Option-Regularized Deep Reinforcement Learning for Cooperative Multi-Agent Online Navigation

arXiv:2601.01155v3 Announce Type: replace Abstract: Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with o

agentsarxiv-cs-ro

Orth-Dion: Eliminating Geometric Mismatch in Distributed Low-Rank Spectral Optimization

arXiv:2605.16341v1 Announce Type: new Abstract: Low-rank gradient compression reduces communication in distributed training by representing updates with rank-r factors. Dion is a recent method that ap

Orthologic for SAT Solving

arXiv:2605.16421v1 Announce Type: cross Abstract: We present a new algorithm for deciding formula entailment in orthologic (a sound approximation of classical logic) that avoids the costly preprocessi

researcharxiv-cs-ai

OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization

arXiv:2605.17757v1 Announce Type: cross Abstract: INT2 KV-cache quantization is attractive for long-context LLM serving, but it remains difficult to make both accurate and deployable. Simple rotations

researcharxiv-cs-ai

OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents

arXiv:2506.16042v2 Announce Type: replace Abstract: Generative AI is being leveraged to solve a variety of computer-use tasks involving desktop applications. State-of-the-art systems have focused sole

🚨Our paper is out in PNAS: we found classic human persuasion techniques worked on AIs in a 'parahuman' way, making them agree to objectiona…

applicationsethan-mollick--x

🚨Our paper is out in PNAS: we found classic human persuasion techniques worked on AIs in a 'parahuman' way, making them agree to objectionable requests (upping compliance from 35% to 51%) It worked on

Local Ai

Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning

arXiv:2605.16391v1 Announce Type: cross Abstract: Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their performance directly det

local-aiarxiv-cs-ai

Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks

arXiv:2605.18583v1 Announce Type: cross Abstract: Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than a

Local Ai

OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism

arXiv:2603.14371v2 Announce Type: replace-cross Abstract: Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, fro

local-aiarxiv-cs-ai

Agents

P2GS: Physical Prior-guided Gaussian Splatting for Photometrically Consistent Urban Reconstruction

arXiv:2605.16925v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently emerged as a powerful explicit representation enabling fast, high-fidelity rendering, making it a promising fo

agentsarxiv-cs-cv

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

arXiv:2605.18587v1 Announce Type: cross Abstract: Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin

PAIR: Prefix-Aware Internal Reward Model for Multi-Turn Agent Optimization

arXiv:2605.17877v1 Announce Type: new Abstract: A significant hurdle for current LLMs is the execution of complex, multi-stage tasks. Group Relative Policy Optimization (GRPO) has been emerging as a l

Pairwise Preference Reward and Group-Based Diversity Enhancement for Superior Open-Ended Generation

arXiv:2605.18191v1 Announce Type: new Abstract: Current reinforcement learning(RL) methods are broadly applicable and powerful in verifiable settings where scalar rewards can be provided. However, in

PaliBench: A Multi-Reference Blueprint for Classical Language Translation Benchmarks

model-releasesarxiv-cs-cl

arXiv:2605.16881v1 Announce Type: new Abstract: Digital humanities projects increasingly rely on machine translation and large language models to widen access to classical, religious, and otherwise un

PanoWorld: A Generative Spatial World Model for Consistent Whole-House Panorama Synthesis

arXiv:2605.17916v1 Announce Type: new Abstract: Generating a consistent whole-house VR tour from a floorplan and style reference requires both photorealistic panoramas and cross-view spatial coherence

PARALLAX: Separating Genuine Hallucination Detection from Benchmark Construction Artifacts

arXiv:2605.17028v1 Announce Type: cross Abstract: Large language models (LLMs) hallucinate with confidence: their outputs can be fluent, authoritative, and simply wrong. In medical, legal, and scienti

Parallel Recursive LSTM

arXiv:2605.17108v1 Announce Type: new Abstract: Transformers have become the dominant architecture for sequence modeling by using self-attention to enable expressive and highly parallel processing. Ho

Parallelizable memory recurrent units

arXiv:2601.09495v3 Announce Type: replace Abstract: With the emergence of massively parallel processing units, parallelization has become a desirable property for new sequence models. The ability to p

Parameter-Efficient Domain Adaptation of Physics-Informed Self-Attention based GNNs for AC Power Flow Prediction

arXiv:2602.18227v2 Announce Type: replace Abstract: Accurate AC power flow (AC-PF) prediction under domain shift is critical when models trained on medium-voltage (MV) grids are deployed on high-volta

Parameterized 4-Qubit EWL Quantum Game Circuits with Dirac-Solow-Swan Hamiltonian Integration for Quadruple Helix Disruptive Innovation Recommender Systems

arXiv:2605.18080v1 Announce Type: cross Abstract: We present a novel parameterized 4-qubit Eisert-Wilkens-Lewenstein (EWL) quantum game circuit for recommender systems in quadruple helix innovation ec

Parameterized Hardness of Zonotope Containment and Neural Network Verification

arXiv:2509.22849v2 Announce Type: replace-cross Abstract: Neural networks with ReLU activations are a widely used model in machine learning. It is thus important to have a profound understanding of th

PAREDA: A Multi-Accent Speech Dataset of Natural Language Processing Research Discussions

arXiv:2605.17860v1 Announce Type: cross Abstract: While modern Automatic Speech Recognition (ASR) systems achieve high accuracy on benchmark corpora, their performance often degrades when there is rea

PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion

arXiv:2511.18801v3 Announce Type: replace Abstract: Existing autoregressive (AR) methods for generating artist-designed meshes struggle to balance global structural consistency with high-fidelity loca

applicationsarxiv-cs-cv

Patch Ensembles for Robust Salmon Re-Identification with Weak Trajectory Labels

arXiv:2605.18038v1 Announce Type: new Abstract: Salmon re-identification in commercial net-pens is challenging due to large populations, which impose strict accuracy requirements and make large-scale

safetyarxiv-cs-cv

Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

arXiv:2605.17719v1 Announce Type: new Abstract: CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dep

Patchwork: A compact representation for 3D polygonal shapes

arXiv:2605.16266v1 Announce Type: cross Abstract: We introduce Patchwork, a new general-purpose shape representation capable of modeling 2D and 3D geometry with a small number of parameters. Patchwork

Patients Speak, AI Listens: LLM-based Analysis of Online Reviews Uncovers Key Drivers for Urgent Care Satisfaction

arXiv:2503.20981v2 Announce Type: replace-cross Abstract: Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey

applicationsarxiv-cs-ai

Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign

arXiv:2605.16452v1 Announce Type: cross Abstract: Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiog