All entries

Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks

arXiv:2511.09048v2 Announce Type: replace Abstract: We propose a novel projection method that guarantees the conservation of integral quantities in Physics-Informed Neural Networks (PINNs). While the

Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning

DGX agent

arXiv:2605.24613v1 Announce Type: cross Abstract: Post-hoc repair of LLM mathematical reasoning introduces an asymmetric risk: fixing an incorrect reasoning trace is useful, but replacing a trace that

researcharxiv-cs-ai

26 May 2026

Guess the Unified Model: How Much Can We Recover from Generated Images?

arXiv:2605.25254v1 Announce Type: cross Abstract: With unified model-generated images now widespread online, attributing their model of origin offers a path toward transparency and deeper insight into

Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory

model-releasesarxiv-cs-lg

arXiv:2605.25509v1 Announce Type: cross Abstract: Reconstructing PDE solutions from sparse observations is a core challenge in scientific computing. We present FM4PDE, a flow-matching generative frame

Hardware

H^{2}MT: Semantic Hierarchy-Aware Hierarchical Memory Transformer

arXiv:2605.24930v1 Announce Type: new Abstract: Transformer-based LLMs achieve strong results on many language tasks; however, long inputs remain challenging because context windows are finite, and pr

hardwarearxiv-cs-cl

Tools

Hackathon 🤝 Music Industry. Introducing the Musicathon by @Musixmatch Pro 💻 Built with support from partners including Replit, @ElevenLabs…

Hackathon 🤝 Music Industry. Introducing the Musicathon by @Musixmatch Pro 💻 Built with support from partners including Replit, @ElevenLabs, @SongstatsApp, @ai_lalal, and @Cyanite_ai. 📆 June 15–21 📍 Fu

toolsreplit--x

Hadamard Representation: Scaffolding Performance Across Model-free RL

model-releasesarxiv-cs-lg

arXiv:2406.09079v5 Announce Type: replace Abstract: Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity fr

Agents

haha sweet, gbrain meets activegraph

haha sweet, gbrain meets activegraph Gbrain is what an agent *knows* — a durable markdown/git knowledge substrate with hybrid search, typed links, facts, timelines, and a real ingestion pipeline. @Act

agentsyohei-nakajima--x

Hardware-Aware Federated Learning for Speech Emotion Recognition

arXiv:2605.24712v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving collaborative training across distributed edge devices, but real deployments involve heterogeneous cl

Harmony in Diversity: Multi-domain Contrastive Policy Optimization for Large Reasoning Models

arXiv:2605.25443v1 Announce Type: new Abstract: Post-training has significantly enhanced the reasoning capability of Large Reasoning Models (LRMs), especially with Reinforcement Learning (RL) like Gro

safetyarxiv-cs-cl

Agents

Harnessing AtomisticSkills for Agentic Atomistic Research

arXiv:2605.24002v1 Announce Type: cross Abstract: Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) hav

agentsarxiv-cs-ai

Industry

Has ChatGPT given YOU a name??

A Reddit discussion in r/ChatGPT where users share their experiences with ChatGPT creating or assigning them personal names during conversations. The thread likely explores whether ChatGPT has a tende

industryr-chatgpt

HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space

arXiv:2509.22299v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures in large language models (LLMs) deliver exceptional performance and reduced inference costs compared to

HeartBeatAI: An Interpretable and Robust Deep Learning Framework for Multi-Label ECG Arrhythmia Detection

arXiv:2605.24588v1 Announce Type: new Abstract: While Deep Learning (DL) enhances automated electrocardiogram (ECG) analysis, clinical deployment is hindered by class imbalance and the generalization

HeLoM: Hierarchical Learning for Whole-Body Loco-Manipulation by a Hexapod Robot

arXiv:2509.23651v3 Announce Type: replace Abstract: In nature, animals often need to move/manipulate objects comparable in weight/size to their own bodies. Compared to grasping and carrying, pushing p

applicationsarxiv-cs-ro

Hera: Learning Long-Horizon Coordination for Device-Cloud Collaborative LLM Agents

arXiv:2605.24598v1 Announce Type: new Abstract: Large language model (LLM) agents excel at solving complex long-horizon tasks through autonomous interaction with environments. However, their real-worl

local-aiarxiv-cs-ai

Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs

arXiv:2605.24774v1 Announce Type: new Abstract: We propose Hermite-NGP, a gradient-augmented multi-resolution hash encoding designed to enable fast and accurate computation of spatial derivatives for

Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio

arXiv:2605.25967v1 Announce Type: new Abstract: As policy catches up with the capabilities of generative AI, watermarking is central to content provenance efforts. Inference-time watermarks for autore

safetyarxiv-cs-lg

Hidden-State Privacy Has an Empty Middle

arXiv:2605.24042v1 Announce Type: cross Abstract: Of 1{,}536 Gaussian release covariances we tested for single-layer hidden-state privacy, zero achieve both moderate utility and moderate privacy again

Hide-and-Shill: A Reinforcement Learning Framework for Market Manipulation Detection in Symphony-a Decentralized Multi-Agent System

arXiv:2507.09179v3 Announce Type: replace Abstract: Decentralized finance (DeFi) has introduced a new era of permissionless financial innovation but also led to unprecedented market manipulation. With

Hide to Guide: Learning via Semantic Masking

arXiv:2605.25198v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a powerful paradigm for improving language models on reasoning-intensive tasks, but i

Hierarchical Local-Global Transformer for Temporal Sentence Grounding

arXiv:2208.14882v2 Announce Type: replace-cross Abstract: This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment

local-aiarxiv-cs-cl

High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications

arXiv:2605.24763v1 Announce Type: new Abstract: This work presents a high-fidelity computational fluid dynamics (CFD) and data-driven modeling framework for assembly-level flow characterization in a f

High-Risk AI Systems and the Problem of Identity in the European AI Act

arXiv:2605.23922v1 Announce Type: cross Abstract: The EU Artificial Intelligence Act (AIA) establishes a lifecycle governance regime for high-risk AI systems built around ex-ante conformity assessment

HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis

arXiv:2509.02113v2 Announce Type: replace-cross Abstract: The advancement of graph-based malware analysis is critically limited by the absence of large-scale datasets that capture the inherent hierarc

HiMed: Incentivizing Hindi Reasoning in Medical LLMs

model-releasesarxiv-cs-cl

arXiv:2605.24635v1 Announce Type: new Abstract: Medical large language models hold promise for reducing healthcare disparities, yet Hindi remains severely underrepresented. While medical LLMs excel in

HiTeC: Hierarchical Contrastive Learning on Text-Attributed Hypergraph with Semantic-Aware Augmentation

arXiv:2508.03104v3 Announce Type: replace-cross Abstract: Contrastive learning (CL) has become a dominant paradigm for self-supervised hypergraph learning, enabling effective training without costly l

applicationsarxiv-cs-ai

HoLoArm: Deformable Arms for Collision-Tolerant Quadrotor Flight

arXiv:2605.25790v1 Announce Type: new Abstract: The increasing use of drones in human-centric applications highlights the need for designs that can survive collisions and recover rapidly, minimizing r

safetyarxiv-cs-ro

HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing

arXiv:2605.24687v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have made significant strides in visual realism and semantic consistency, yet they often perpetuate and amplify societal bi

Industry

How AI startups like Altur are using chatbots to help automate debt collection; YC incubated six debt collection and settlement startups in the past six years (Kate Knibbs/Wired)

Kate Knibbs / Wired: How AI startups like Altur are using chatbots to help automate debt collection; YC incubated six debt collection and settlement startups in the past six years — There's a mad dash

industrytechmeme

How does Bayesian Sampling help Membership Inference Attacks?

arXiv:2503.07482v2 Announce Type: replace-cross Abstract: Membership Inference Attacks (MIAs) aim to estimate whether a specific data point was used in the training of a given model. Existing state-of

How Many Tools Should an LLM Agent See? A Chance-Corrected Answer

arXiv:2605.24660v1 Announce Type: cross Abstract: Before an LLM agent can use a tool, a retrieval system must decide which candidate tools to show to the agent. How long should that shortlist be? Show

How Much Do Large Language Model Cheat on Evaluation? Benchmarking Overestimation under the One-Time-Pad-Based Framework

model-releasesarxiv-cs-cl

arXiv:2507.19219v2 Announce Type: replace Abstract: Overestimation in evaluating large language models (LLMs) has become an increasing concern. Due to the contamination of public benchmarks or imbalan

How Much Structure Do LLMs Need? Evaluating LLMs for Bibliometric Cluster Description

arXiv:2605.24351v1 Announce Type: new Abstract: Large language models (LLMs) can support scientific literature synthesis, but remain prone to hallucinated references, uneven coverage, and weakly groun

safetyarxiv-cs-cl

How Much Thinking is Enough? Quantifying and Understanding Redundancy in LLM Reasoning

arXiv:2605.23926v1 Announce Type: new Abstract: Reasoning-capable large language models solve hard problems by emitting long chains of thought, paying heavily in latency, GPU time, and energy. Casual

How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis

arXiv:2605.24749v1 Announce Type: cross Abstract: Reward modeling is not only a prediction problem: in KL-regularized policy optimization, the learned reward is exponentiated to define the deployed po

safetyarxiv-cs-lg

Tutorials

How Should LLMs Consume High-Quality Data? Optimal Data Scheduling via Quality-Aware Functional Scaling Laws

arXiv:2605.25698v1 Announce Type: cross Abstract: High-quality data is scarce in large language model (LLM) training, yet how to schedule its use jointly with training dynamics lacks theoretical guida

tutorialsarxiv-cs-ai

How to Mitigate the Distribution Shift Problem in Robotics Control: A Robust and Adaptive Approach Based on Offline to Online Imitation Learning

arXiv:2605.25414v1 Announce Type: new Abstract: Distribution shift in imitation learning refers to the problem that the agent cannot plan proper actions for a state that has not been visited during th

safetyarxiv-cs-ro

How to ship a local LLM that matches frontier LLMs with evals and prompt engineering

Most production AI features don't need a frontier model. Here's how capability evals and prompt engineering can help ship a local SLM that matches frontier-model quality with lower latency and cost. T

local-aiarize-ai

Tutorials

How to use Grok Build

How to use Grok Build Beginner video: How to install & use Grok Build (made for non-technical SuperGrok and X Premium+ users) I got so many questions from friends, so I made this simple step-by-step g

tutorialselon-musk--x

How we evolved Google’s global and data center networks for the AI era

model-releasesgoogle-cloud-ai

Over the last 25 years of building Google’s global network, we’ve navigated major architectural eras — from the Internet, to streaming, and the cloud. Today, we are squarely in the midst of a fourth:

How Well Do Models Follow Their Constitutions?

arXiv:2605.24229v1 Announce Type: new Abstract: Frontier AI developers now train models against long written behavioral specifications, such as Anthropic's constitution (Anthropic, 2025a) and OpenAI's

Huge one for developers building with AI. Excited to announce @ClementDelangue (CEO @huggingface) is joining DASH 2026 for a fireside chat w…

applicationsclem-delangue--x

Huge one for developers building with AI. Excited to announce @ClementDelangue (CEO @huggingface) is joining DASH 2026 for a fireside chat with @oliveur. Open source changed software, open models are

Huge thanks to @ComfyUI for publishing a deep-dive case study on how we’re building enterprise-grade, scalable AI pipelines. Arron Award Win…

Huge thanks to @ComfyUI for publishing a deep-dive case study on how we’re building enterprise-grade, scalable AI pipelines. Arron Award Winning work for AI workflow. Read the full breakdown: https://

applicationscomfyui--x

Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment

arXiv:2605.24180v1 Announce Type: cross Abstract: Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally

applicationsarxiv-cs-ai

Industry

Human Archive, which trains robots using first-person video from 1,000+ camera-equipped caps worn by Indian home services workers, raised $8.2M from YC and more (Ivan Mehta/TechCrunch)

Ivan Mehta / TechCrunch: Human Archive, which trains robots using first-person video from 1,000+ camera-equipped caps worn by Indian home services workers, raised $8.2M from YC and more — In the last

industrytechmeme

Human in the loop 🤖 Made in @ComfyUI with a laundry list of tools: @ltx_model 2.3 + @thesystms FLW LoRA, @Alibaba_Wan 2.2 I2V + T2V, Floren…

Human in the loop 🤖 Made in @ComfyUI with a laundry list of tools: @ltx_model 2.3 + @thesystms FLW LoRA, @Alibaba_Wan 2.2 I2V + T2V, Florence2, @Meta Sapiens2, @OpenAI GPT Image 2.0, @suno , @AdobeAE

local-aicomfyui--x

HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos

arXiv:2605.24934v1 Announce Type: cross Abstract: Human egocentric video captures rich manipulation demonstrations without any robot hardware, yet transferring these skills to robots remains challengi