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HandAnthro: Automated Hand Anthropometry from a Single Image

arXiv:2609.37855v1 Announce Type: cross Abstract: Hand anthropometry supports protective-glove design, but existing measurement methods often require trained operators, specialized hardware, or manual

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Safety

Hands-on with Dots, OpenAI's work-focused agentic product: highly capable and intuitive, with natural-feeling conversations represented as a chat inside ChatGPT (Casey Newton/Platformer)

DGX agent

Casey Newton / Platformer: Hands-on with Dots, OpenAI's work-focused agentic product: highly capable and intuitive, with natural-feeling conversations represented as a chat inside ChatGPT — With safet

safetytechmeme

30 Sept 2026

HaPRL: Human-Anchored Process Reinforcement Learning for Visual Search Agent

arXiv:2609.37190v1 Announce Type: new Abstract: Multi-turn visual search agents answer questions about high-resolution images by iteratively deciding where to look. Reinforcement learning for these ag

agentsarxiv-cs-cv

Hardware

Hardware-Aware Functional Kolmogorov-Arnold Networks for Efficient Medical Image Enhancement and Segmentation

arXiv:2609.36134v1 Announce Type: new Abstract: Functional Kolmogorov-Arnold Networks (FunKAN) achieve state-of-the-art accuracy on MRI Gibbs artifact removal and anatomical segmentation, but their 11

hardwarearxiv-cs-cv

Local Ai

HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment

arXiv:2609.38006v1 Announce Type: new Abstract: Running a language model locally offers advantages in privacy, latency, and cost, but local hardware fits only small models, which are less capable than

local-aiarxiv-cs-ai

HARMONI: Aligning Human and Scene Priors for Multi-View 4D Reconstruction

arXiv:2603.12789v3 Announce Type: replace Abstract: Recent advances in 3D foundation models have enabled joint reconstruction of humans and their surrounding environments. However, combining independe

researcharxiv-cs-cv

Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

arXiv:2609.36892v1 Announce Type: new Abstract: As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful

Applications

Harnessing Large Language Models to Compile Task-Relevant Context into Bayesian Optimisation

arXiv:2609.36788v1 Announce Type: new Abstract: Incorporating rich task-relevant context, such as domain knowledge and external observations, is a key capability yet remains challenging for Bayesian o

applicationsarxiv-cs-lg

HeadGuard: Selective Head Protection for Low-Bit VLM KV-Cache Quantization

model-releasesarxiv-cs-cv

arXiv:2609.35800v1 Announce Type: cross Abstract: Low-bit key-value (KV) cache quantization saves storage but can sharply degrade vision-language model (VLM) accuracy. We introduce HeadGuard, a compos

HEAR: Real Voices, Real Bias: A Large-Scale Human-Recorded, Demographically Diverse Benchmark for Audio Language Models

arXiv:2609.35952v1 Announce Type: cross Abstract: We introduce HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising 87k real huma

HEIR: Learning Human-Entity Interactions with Functional Roles

model-releasesarxiv-cs-cv

arXiv:2609.35955v1 Announce Type: new Abstract: Understanding human-entity interactions requires recovering each person-action event's participants, roles, and shared identities. This structure can su

Hardware

HelixWorld: A Real-time Interactive Audio-Visual World Model

arXiv:2609.38123v1 Announce Type: new Abstract: World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time. Yet prevailing interactive world models r

hardwarearxiv-cs-cv

Here’s what AI leaders are saying about Trump’s new safety plan

After hosting a meal with Big Tech leaders on Tuesday, President Donald Trump responded to journalist questions about his artificial intelligence announcements in typical fashion. He said his previous

safetythe-verge-ai

Here’s how tech leaders will self-police AI safety under Trump’s deal

We now have the full details of the 'morally binding' AI safety deal announced by President Trump yesterday, in which top executives agreed to self-regulate their artificial intelligence technology. T

safetythe-verge-ai

HERO: Histology Encoder for Robust Representation in Oncology

model-releasesarxiv-cs-cv

arXiv:2609.35943v1 Announce Type: new Abstract: Foundation models trained on large pathology image corpora now provide strong, transferable representations for computational pathology. Over the past f

HeurEvo: Agentic Evolution of Hybrid Solver-Augmented Heuristics for Time-Critical Mathematical Optimization

arXiv:2609.36303v1 Announce Type: new Abstract: Recent advances in agentic heuristic design use AI agents and execution feedback to automate algorithm discovery for challenging optimization problems.

agentsarxiv-cs-cl

Industry

HF is the perfect place to host your big robotics datasets Read how we do it here : https://huggingface.co/spaces/imstevenpmwork/LeRobot_and…

Hugging Face (HF) provides a platform designed to host large‑scale robotics datasets. An example implementation can be seen in the space at `https://huggingface.co/spaces/imstevenpmwork/LeRobot_and…`,

industryclem-delangue--x

Hidden Reasoning Must Leak, but Need Not Be Readable: Fundamental Opportunities and Limits for Chain-of-Thought Monitoring

arXiv:2609.37312v1 Announce Type: cross Abstract: Can reasoning models trick chain of thought (CoT) monitors and perform hidden computation without revealing it in their thinking traces? We show that

Hierarchical Compression of Vision-Language Model Benchmarks

arXiv:2609.37515v1 Announce Type: cross Abstract: Thorough evaluation of vision-language models (VLMs) has become prohibitively expensive, as benchmarks span an ever-broader spectrum of capabilities a

Hierarchical Utility Calibration for Structured Multiclass Decisions

arXiv:2609.36532v1 Announce Type: cross Abstract: In multiclass probabilistic prediction, Utility Calibration (UC), which focuses auditing on specified utilities, has recently received attention as a

High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations

arXiv:2512.15684v2 Announce Type: replace-cross Abstract: Partial Least Squares (PLS) is a widely used method for data integration, designed to extract latent components shared across paired high-dime

safetyarxiv-cs-lg

High-Dimensional Simulation-Based Inference in Latent Spaces

model-releasesarxiv-cs-lg

arXiv:2609.37381v1 Announce Type: new Abstract: Neural simulation-based inference (SBI) has been widely successful in inferring a relatively small number of interpretable parameters from potentially h

High-Probability Convergence of Clipped SGD under Heavy-Tailed Noise and (L_0,L_1)-Smoothness

arXiv:2505.20817v3 Announce Type: replace-cross Abstract: Gradient clipping is widely used in language-model training to control heavy-tailed gradient noise and can improve convergence guarantees over

safetyarxiv-cs-lg

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

HiRAE: Hierarchical Representation Autoencoding with Residual Budgets

arXiv:2609.37775v1 Announce Type: cross Abstract: Pretrained visual representations support image generation, but may not fully preserve the fine-grained details needed for faithful reconstruction. Me

safetyarxiv-cs-ai

HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation

arXiv:2609.36559v1 Announce Type: cross Abstract: Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early

Homo-RAG: Homology-Guided Retrieval-Augmented Generation for Cross-Species Gene Function Prediction

arXiv:2608.25466v2 Announce Type: replace-cross Abstract: The functional annotation of genes in non-model organisms remains a significant challenge in computational biology, with 20-70% of sequenced g

Honeycomb: Constant-Size Scene Memory Representation for Video World Models

arXiv:2609.37690v1 Announce Type: new Abstract: Video world models require persistent scene memory to maintain consistency during long-horizon video generation. Existing spatial memory systems accumul

researcharxiv-cs-cv

Tutorials

HorizonFlow: Variable-Length Planning for Offline Goal-Conditioned RL

arXiv:2609.36896v1 Announce Type: new Abstract: Recent advances in generative planning have made trajectory inpainting a promising approach to offline goal-conditioned reinforcement learning. However,

tutorialsarxiv-cs-ai

How Can Recommendation Feedback Evolve Agent Memory?

arXiv:2609.37544v1 Announce Type: new Abstract: Content-generation agents continuously receive impressions, clicks, conversions, and negative feedback from recommendation systems, providing real-world

How Language Models Differ in Redistributing Attention-Head Activity Under Serial Demand

model-releasesarxiv-cs-lg

arXiv:2609.36221v1 Announce Type: new Abstract: The way a model distributes activity over each layer's attention heads offers a coarse view of how it routes information through depth; how this changes

How Local Mixing Encodes Relative Position in Global NoPE Attention

arXiv:2609.38109v1 Announce Type: cross Abstract: The attention operation is naively position invariant. However, positional information is fundamental to natural language, and therefore a variety of

safetyarxiv-cs-ai

How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification

model-releasesarxiv-cs-cl

arXiv:2609.37882v1 Announce Type: new Abstract: Every text classifier for an African language begins with a budgeting question: how many labelled examples are needed, and can labels from other African

How many people show up on a Tuesday night to talk about document processing for AI agents? 🤔 In New York, enough to fill the room and star…

How many people show up on a Tuesday night to talk about document processing for AI agents? 🤔 In New York, enough to fill the room and start a waitlist. In San Francisco, almost 600. We were in both c

agentsjerry-liu--x

How Medical VLMs Underutilize Their Vision Encoders: A Dermatology Perspective

arXiv:2609.36557v1 Announce Type: cross Abstract: Medical Vision-Language Models (VLMs) show significant promise for clinical image understanding, offering accurate diagnosis with interpretable reason

Applications

How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp

applicationsarxiv-cs-ai

How smart is the IQ3 family of Qwen 3.8 Flash Next for coding tasks?

model-releasesr-localllama

I've been closely following the rise of the Strata inference engine and as someone with 28GB VRAM and 32GB RAM I'm itching to buy 32GB more RAM just to use Flash Next. But of course before I make such

How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats

arXiv:2609.35815v1 Announce Type: cross Abstract: Researchers across academia increasingly base significance claims on LLM judge scores and small-sample AI evaluations. Yet without well-calibrated con

safetyarxiv-cs-ai

How to scale agentic applications without creating AI sprawl

**Summary:** The article titled *“How to scale agentic applications without creating AI sprawl”* is currently incomplete, containing only placeholder text (“Buil Buil Buil”). No substantive guidance o

agentsdatabricks

Human-AI Collaboration: From Paradoxes to Patterns

arXiv:2609.36481v1 Announce Type: new Abstract: Evidence shows that humans and AI systems perform better together, by collaborating, than alone. This paper examines two key design dimensions of human-

Human-inspired, Task-Dimension-Guided Exploration for Efficient Learning in High Dimensions

arXiv:2609.36672v2 Announce Type: new Abstract: Efficient exploration in high-dimensional decision spaces remains a central challenge for decision-making systems. Humans, in contrast, can navigate lar

Hybrid Ensemble Learning for EEG-Based Epileptic Seizure Forecasting

arXiv:2609.35876v1 Announce Type: new Abstract: Epileptic seizure forecasting aims to provide actionable warnings before seizure onset, yet patient-independent generalization and false-alarm control r

Hybrid Feature Learning for Handwriting Verification

arXiv:1812.02621v2 Announce Type: replace Abstract: We propose an effective Hybrid Deep Learning (HDL) architecture for the task of determining the probability that a questioned handwritten word has b

researcharxiv-cs-cv

Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest

model-releasesarxiv-cs-lg

arXiv:2609.37308v1 Announce Type: cross Abstract: This paper introduces a hybrid joint-selective optimization (HJSO) framework for large-scale numerical problems in which a small subset of trainable q

Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios

arXiv:2609.36044v1 Announce Type: cross Abstract: We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the c

Tutorials

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

arXiv:2609.38008v1 Announce Type: new Abstract: Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical use

tutorialsarxiv-cs-cv

HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classification

arXiv:2609.37740v1 Announce Type: new Abstract: While attaining remarkable results for many applications, Deep Learning models are notoriously difficult to explain. This work introduces HyDI, a hybrid

Hyper Yoshimura: How a slight tweak on a classical folding pattern unleashes meta-stability for deployable robots

arXiv:2505.09919v3 Announce Type: replace Abstract: Deployable structures inspired by origami have provided lightweight, compact, and reconfigurable solutions for various robotic and architectural app

researcharxiv-cs-ro