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Handwriting Trajectory Recovery with Diffusion Models

arXiv:2607.03422v1 Announce Type: new Abstract: Recovering online pen trajectories from offline handwriting images, often referred to as handwriting trajectory recovery (stroke recovery), is an offlin

researcharxiv-cs-cv

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Harmonic-Aware Transformer for Real-Time Catheter Localization in Interventional Procedures of Magnetic Particle Imaging

DGX agent

arXiv:2607.02919v1 Announce Type: cross Abstract: Magnetic particle imaging (MPI) enables real-time, radiation-free tracking of magnetic nanoparticle-coated instruments, making it highly suitable for

local-aiarxiv-cs-ai

7 Jul 2026

Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions

arXiv:2607.03935v1 Announce Type: new Abstract: Self-evolving frameworks usually optimize task solutions while treating the surrounding harness as fixed. We introduce Harness-Aware Self-Evolving (HASE

HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation

arXiv:2607.04329v1 Announce Type: new Abstract: Large language models increasingly operate in settings where humans are active collaborators rather than passive task providers. We introduce HAS-Framew

HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy

arXiv:2607.04353v1 Announce Type: cross Abstract: Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell image

HCSU: A Dataset and Benchmark for Fine-Grained Historical Calligraphy Style Understanding

arXiv:2607.04147v1 Announce Type: cross Abstract: Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision

HeartVolMesh: Cardiac Volumetric Mesh Reconstruction via Covariance-Guided Graph Deformation

arXiv:2607.04243v1 Announce Type: new Abstract: Accurate patient-specific tetrahedral cardiac meshes are essential for in-silico trials, yet common segmentation-then-modelling pipelines can blur thin-

safetyarxiv-cs-cv

Agents

Heaviside Continuity of Rolling Coefficients for Eliminating Epistemic Entropy in Large Language Models

arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro

agentsarxiv-cs-ai

Heterogeneous Graph Condensation via Role-Aware Clustering

arXiv:2607.03097v1 Announce Type: new Abstract: Heterogeneous Graph Neural Networks (HGNNs) have exhibited remarkable efficacy in modeling complex systems with multiple types of nodes and relations, y

researcharxiv-cs-lg

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

arXiv:2607.02038v2 Announce Type: replace Abstract: The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious

tutorialsarxiv-cs-cv

Hierarchical Bayesian Crowdsourcing with Item Difficulty

model-releasesarxiv-cs-lg

arXiv:2405.19521v3 Announce Type: replace Abstract: In applied statistics and machine learning, the gold standards used for training are often biased and almost always noisy. Dawid and Skene's justifi

Hierarchical Evidence-Driven Reasoning for Long Document Understanding

arXiv:2607.04625v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) streamlines long-document understanding by leveraging retrieval mechanisms to restrict input images to a highly c

Local Ai

Hierarchical Multi-Agent Reinforcement Learning for Carbon-Aware AI Data Centers in Power Distribution Systems

arXiv:2607.03324v1 Announce Type: cross Abstract: Eco-friendly energy management for artificial intelligence data centers (AIDCs) is crucial because of the significant increase in energy consumption-i

local-aiarxiv-cs-ai

Hierarchical Multi-to-Single-Modal Knowledge Distillation for Disruption Prediction in EAST

arXiv:2607.04241v1 Announce Type: cross Abstract: Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible

Hierarchical Scaffolding Enables Human-Like Cognitive Selectivity under Data Scarcity

arXiv:2607.04709v1 Announce Type: cross Abstract: Modern machine learning systems demand extensive datasets for visual recognition. Conversely, humans learn with high efficiency despite severe data li

tutorialsarxiv-cs-cv

Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling

arXiv:2607.02980v1 Announce Type: cross Abstract: Scaling modern large language models (LLMs) to long contexts is limited by the quadratic computation cost, and poor length extrapolation of dense atte

HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference

arXiv:2607.04302v1 Announce Type: cross Abstract: We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on

High-Fidelity One-Step Generative Visuomotor Policy via Recursive Correction, Frequency Consistency, and Contrastive Flow Matching

arXiv:2607.03865v1 Announce Type: cross Abstract: Generative models such as diffusion and flow matching have advanced robotic visuomotor policies by modeling multimodal action distributions, but their

safetyarxiv-cs-ai

High-Precision Formation Control for Heterogeneous Multi-Robot Systems via Hierarchical Hybrid Physics-Informed Deep Reinforcement Learning

arXiv:2607.03512v1 Announce Type: new Abstract: Existing classical control methods commonly require precise models and struggle to cope with model uncertainties and external disturbances, while end-to

safetyarxiv-cs-ro

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders

arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i

applicationsarxiv-cs-cl

Holo-Captioning: Toward the Text Equivalent of 3D Scenes

model-releasesarxiv-cs-cv

arXiv:2607.02908v1 Announce Type: new Abstract: This work introduces holo-captioning, a novel task that strives to seek the text equivalent of 3D scenes. As the initial step, we formulate holo-caption

Agents

Homer: Understanding Long-form Videos with Hierarchical Memory and Agentic Reasoning

arXiv:2607.02588v1 Announce Type: cross Abstract: Multimodal large language models excel on short clips but struggle on hour-long videos in an online setting, where frames are processed incrementally

agentsarxiv-cs-ai

Hope for the Best, Prepare for the Worst: Occlusion-Aware Contingency Planning for Autonomous Vehicles

arXiv:2607.03155v1 Announce Type: new Abstract: The deployment of autonomous vehicles in urban environments introduces significant safety challenges, particularly in scenarios with occlusions, where c

safetyarxiv-cs-ro

How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation

arXiv:2607.03831v1 Announce Type: cross Abstract: Diffusion models have recently been repurposed for zero-shot classification, giving rise to diffusion classifiers that identify the best-matching text

How Far is Too Far? Defining the Distance Threshold for Verification Siamese Networks

arXiv:2607.05329v1 Announce Type: new Abstract: Siamese verification networks are widely used to compare items such as faces, cars, or signatures. In these scenarios, the network is trained to learn a

tutorialsarxiv-cs-lg

How Many Initial Points Does Bayesian Optimization Need?

arXiv:2607.04356v1 Announce Type: new Abstract: Bayesian Optimization (BO) generally begins with an initialization phase: a batch of n_0 uninformed evaluations. The choice of n_0 remains largely heuri

researcharxiv-cs-lg

How Many Iterations to Jailbreak? Dynamic Budget Allocation for Multi-Turn LLM Evaluation

model-releasesarxiv-cs-lg

arXiv:2605.06605v2 Announce Type: replace Abstract: Evaluating and predicting the performance of large language models (LLMs) in multi-turn conversational settings is critical yet computationally expe

How many labels do you need? A decision framework for cross-habitat marine species recognition

model-releasesarxiv-cs-cv

arXiv:2607.02559v1 Announce Type: new Abstract: Automated image recognition is increasingly used to scale ecological monitoring beyond manual annotation, yet ecologists lack evidence-based guidance on

How Much is Left? LLMs Linearly Encode Their Remaining Output Length

arXiv:2607.05316v1 Announce Type: new Abstract: Large language models generate one token at a time, yet their responses show remarkably consistent length structure: step-by-step solutions converge in

tutorialsarxiv-cs-cl

How Much of the Routing Gap Is Real? Decomposing the Router-to-Oracle Gap into Reproducible Specialist Advantage and Single-Draw Label Noise

model-releasesarxiv-cs-lg

arXiv:2607.03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instan

How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs

arXiv:2607.03561v1 Announce Type: new Abstract: As AI models continue to develop powerful capabilities, it becomes critical that we are able to verify that their output is aligned with our intentions.

safetyarxiv-cs-ai

How to Build Digital Humans? From Priors to Photorealistic Avatars

arXiv:2607.04341v1 Announce Type: cross Abstract: This state-of-the-art report provides an overview of controllable 3D human avatar creation. We describe current 3D avatar systems, which typically con

tutorialsarxiv-cs-cl

How Utilitarian Are OpenAI's Models Really? Replicating and Reinterpreting Pfeffer, Krugel, and Uhl (2025)

arXiv:2603.22730v2 Announce Type: replace Abstract: Pfeffer, Krugel, and Uhl (2025) report that OpenAI's reasoning model o1-mini produces more utilitarian responses to the trolley problem and footbrid

safetyarxiv-cs-cl

HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors

arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt

applicationsarxiv-cs-ro

Human-Centric Reflective Architecture for Human-AI Collaborative Decision-Making

arXiv:2607.03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhan

safetyarxiv-cs-ai

Human-like Object Grouping in Self-supervised Vision Transformers

arXiv:2603.13994v2 Announce Type: replace-cross Abstract: Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object s

Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation

arXiv:2510.08807v3 Announce Type: replace-cross Abstract: From loco-motion to dextrous manipulation, humanoid robots have made remarkable strides in demonstrating complex full-body capabilities. Howev

safetyarxiv-cs-lg

Agents

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

arXiv:2607.04884v1 Announce Type: new Abstract: We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, informati

agentsarxiv-cs-cv

HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis

arXiv:2603.01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable c

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

applicationsarxiv-cs-cv

Hyper-KGGen: A Skill-Driven Knowledge Extractor for High-Quality Knowledge Hypergraph Generation

model-releasesarxiv-cs-cl

arXiv:2602.19543v2 Announce Type: replace Abstract: Knowledge hypergraphs surpass traditional binary knowledge graphs by encapsulating complex n-ary atomic facts, providing a more comprehensive paradi

Hyperparameter Transfer in Graph Neural Networks

arXiv:2607.05017v1 Announce Type: cross Abstract: The performance of deep learning models crucially depends on the settings of hyperparameters like learning rate, initialization scale, and weight deca

Hardware

HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion

arXiv:2607.03012v1 Announce Type: cross Abstract: Video Diffusion Transformers (VDiTs) have demonstrated significant capabilities in high-fidelity video generation. However, their ability to produce l

hardwarearxiv-cs-ai

i-IF-Learn: Iterative Feature Selection and Unsupervised Learning for High-Dimensional Complex Data

arXiv:2603.24025v2 Announce Type: replace Abstract: Unsupervised learning of high-dimensional data is challenging due to irrelevant or noisy features obscuring underlying structures. It's common that

tutorialsarxiv-cs-lg

IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition

arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and

applicationsarxiv-cs-cv

ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

model-releasesarxiv-cs-cv

arXiv:2607.04675v1 Announce Type: new Abstract: This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Gra

ICR-RL: Deep Reinforcement Learning via In-Context Regression

arXiv:2509.11259v2 Announce Type: replace-cross Abstract: Recent advancements in machine learning have largely been driven by foundation models (FMs) trained on large, diverse datasets, enabling them