All entries

H-SPAM: Hierarchical Superpixel Anything Model

arXiv:2604.11218v1 Announce Type: new Abstract: Superpixels offer a compact image representation by grouping pixels into coherent regions. Recent methods have reached a plateau in terms of segmentatio

Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2604.11430v1 Announce Type: cross Abstract: AI agents that pay for resources via the x402 protocol embed payment metadata - resource URLs, descriptions, and reason strings - in every HTTP paymen

agentsarxiv-cs-ai

14 Apr 2026

Hardware

Hardware Utilization and Inference Performance of Edge Object Detection Under Fault Injection

arXiv:2604.09631v1 Announce Type: cross Abstract: As deep learning models are deployed on resource constrained edge platforms in autonomous driving systems, reli able knowledge of hardware behavior un

hardwarearxiv-cs-ai

Harnessing Photonics for Machine Intelligence

arXiv:2604.10841v1 Announce Type: cross Abstract: The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivatin

tutorialsarxiv-cs-ai

HDR 3D Gaussian Splatting via Luminance-Chromaticity Decomposition

model-releasesarxiv-cs-cv

arXiv:2511.12895v2 Announce Type: replace Abstract: High Dynamic Range (HDR) 3D reconstruction is pivotal for professional content creation in filmmaking and virtual production. Existing methods typic

Safety

HDR Video Generation via Latent Alignment with Logarithmic Encoding

arXiv:2604.11788v1 Announce Type: new Abstract: High dynamic range (HDR) imagery offers a rich and faithful representation of scene radiance, but remains challenging for generative models due to its m

safetyarxiv-cs-cv

Applications

Head-wise Modality Specialization within MLLMs for Robust Fake News Detection under Missing Modality

arXiv:2604.09711v1 Announce Type: cross Abstract: Multimodal fake news detection (MFND) aims to verify news credibility by jointly exploiting textual and visual evidence. However, real-world news diss

applicationsarxiv-cs-cl

HealthAdminBench: Evaluating Computer-Use Agents on Healthcare Administration Tasks

arXiv:2604.09937v1 Announce Type: new Abstract: Healthcare administration accounts for over $1 trillion in annual spending, making it a promising target for LLM-based computer-use agents (CUAs). While

HearthNet: Edge Multi-Agent Orchestration for Smart Homes

arXiv:2604.09618v1 Announce Type: cross Abstract: Smart-home users increasingly want to control their homes in natural language rather than assemble rules, dashboards, and API integrations by hand. At

HeceTokenizer: A Syllable-Based Tokenization Approach for Turkish Retrieval

arXiv:2604.10665v1 Announce Type: new Abstract: HeceTokenizer is a syllable-based tokenizer for Turkish that exploits the deterministic six-pattern phonological structure of the language to construct

HECTOR: Human-centric Hierarchical Coordination and Supervision of Robotic Fleets under Continual Temporal Tasks

arXiv:2604.10892v1 Announce Type: new Abstract: Robotic fleets can be extremely efficient when working concurrently and collaboratively, e.g., for delivery, surveillance, search and rescue. However, i

tutorialsarxiv-cs-ro

Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement

arXiv:2604.09579v1 Announce Type: new Abstract: In large-scale cloud service platforms, thousands of customer tickets are generated daily and are typically handled through on-call dialogues. This high

agentsarxiv-cs-ai

Heterogeneous Connectivity in Sparse Networks: Fan-in Profiles, Gradient Hierarchy, and Topological Equilibria

model-releasesarxiv-cs-lg

arXiv:2604.10560v1 Announce Type: new Abstract: Profiled Sparse Networks (PSN) replace uniform connectivity with deterministic, heterogeneous fan-in profiles defined by continuous, nonlinear functions

Heterogeneous Consensus-Progressive Reasoning for Efficient Multi-Agent Debate

arXiv:2604.09679v1 Announce Type: cross Abstract: Multi-Agent Debate (MAD) is a collaborative framework in which multiple agents iteratively refine solutions through the generation of reasoning and al

agentsarxiv-cs-ai

HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images

arXiv:2412.20704v2 Announce Type: replace Abstract: Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-genera

HG-Lane: High-Fidelity Generation of Lane Scenes under Adverse Weather and Lighting Conditions without Re-annotation

model-releasesarxiv-cs-cv

arXiv:2603.10128v2 Announce Type: replace Abstract: Lane detection is a crucial task in autonomous driving, as it helps ensure the safe operation of vehicles. However, existing datasets such as CULane

Hidden Failures in Robustness: Why Supervised Uncertainty Quantification Needs Better Evaluation

arXiv:2604.11662v1 Announce Type: new Abstract: Recent work has shown that the hidden states of large language models contain signals useful for uncertainty estimation and hallucination detection, mot

HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement

arXiv:2604.10675v1 Announce Type: new Abstract: We propose a method to learn explicit, class-conditioned spatial priors for object placement in natural scenes by distilling the implicit placement know

Hide-and-Seek Attribution: Weakly Supervised Segmentation of Vertebral Metastases in CT

arXiv:2512.06849v2 Announce Type: replace Abstract: Accurate segmentation of vertebral metastasis in CT is clinically important yet difficult to scale, as voxel-level annotations are scarce and both l

HiEdit: Lifelong Model Editing with Hierarchical Reinforcement Learning

arXiv:2604.11214v1 Announce Type: new Abstract: Lifelong model editing (LME) aims to sequentially rectify outdated or inaccurate knowledge in deployed LLMs while minimizing side effects on unrelated i

Hierarchical Textual Knowledge for Enhanced Image Clustering

arXiv:2604.11144v1 Announce Type: cross Abstract: Image clustering aims to group images in an unsupervised fashion. Traditional methods focus on knowledge from visual space, making it difficult to dis

tutorialsarxiv-cs-cl

Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution

arXiv:2604.10271v1 Announce Type: cross Abstract: In what way could a data breach involving government-issued IDs such as passports, driver's licenses, etc., rival a random voluntary disclosure on a n

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation

arXiv:2510.07794v2 Announce Type: replace-cross Abstract: Agentic RAG is a powerful technique for incorporating external information that LLMs lack, enabling better problem solving and question answer

HistLens: Mapping Idea Change across Concepts and Corpora

arXiv:2604.11749v1 Announce Type: new Abstract: Language change both reflects and shapes social processes, and the semantic evolution of foundational concepts provides a measurable trace of historical

HO-Flow: Generalizable Hand-Object Interaction Generation with Latent Flow Matching

arXiv:2604.10836v1 Announce Type: new Abstract: Generating realistic 3D hand-object interactions (HOI) is a fundamental challenge in computer vision and robotics, requiring both temporal coherence and

Hodoscope: Unsupervised Monitoring for AI Misbehaviors

arXiv:2604.11072v1 Announce Type: new Abstract: Existing approaches to monitoring AI agents rely on supervised evaluation: human-written rules or LLM-based judges that check for known failure modes. H

HOG-Layout: Hierarchical 3D Scene Generation, Optimization and Editing via Vision-Language Models

arXiv:2604.10772v1 Announce Type: new Abstract: 3D layout generation and editing play a crucial role in Embodied AI and immersive VR interaction. However, manual creation requires tedious labor, while

Applications

House of Dextra: Cross-embodied Co-design for Dexterous Hands

arXiv:2512.03743v5 Announce Type: replace-cross Abstract: Dexterous manipulation is limited by both control and design, without consensus as to what makes manipulators best for performing dexterous ta

applicationsarxiv-cs-lg

How Alignment Routes: Localizing, Scaling, and Controlling Policy Circuits in Language Models

arXiv:2604.04385v3 Announce Type: replace-cross Abstract: This paper localizes the policy routing mechanism in alignment-trained language models. An intermediate-layer attention gate reads detected co

How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities

arXiv:2603.02578v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive domains, yet their unpredictable behaviors, ranging from misalign

How LLMs Might Think

arXiv:2604.09674v1 Announce Type: new Abstract: Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently developed an argument from rationality for the claim that LL

researcharxiv-cs-ai

How Many Tries Does It Take? Iterative Self-Repair in LLM Code Generation Across Model Scales and Benchmarks

arXiv:2604.10508v1 Announce Type: cross Abstract: Large language models frequently fail to produce correct code on their first attempt, yet most benchmarks evaluate them in a single-shot setting. We i

How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical Contexts

arXiv:2604.11133v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being explored for clinical question answering and decision support, yet safe deployment critically requir

How to Bridge the Sim-to-Real Gap in Digital Twin-Aided Telecommunication Networks

arXiv:2507.07067v3 Announce Type: replace-cross Abstract: Training effective artificial intelligence models for telecommunications is challenging due to the scarcity of deployment-specific data. Real

tutorialsarxiv-cs-lg

How to Design a Compact High-Throughput Video Camera?

arXiv:2604.10619v1 Announce Type: new Abstract: High throughput video acquisition is a challenging problem and has been drawing increasing attention. Existing high throughput imaging systems splice hu

How to Spin an Object: First, Get the Shape Right

arXiv:2412.10273v3 Announce Type: replace Abstract: Image-to-3D models increasingly rely on hierarchical generation to disentangle geometry and texture. However, the design choices underlying these tw

How You Ask Matters! Adaptive RAG Robustness to Query Variations

arXiv:2604.10745v1 Announce Type: new Abstract: Adaptive Retrieval-Augmented Generation (RAG) promises accuracy and efficiency by dynamically triggering retrieval only when needed and is widely used i

HTAA: Enhancing LLM Planning via Hybrid Toolset Agentization & Adaptation

arXiv:2604.10917v1 Announce Type: new Abstract: Enabling large language models to scale and reliably use hundreds of tools is critical for real-world applications, yet challenging due to the inefficie

agentsarxiv-cs-cl

Safety

Hubble: An LLM-Driven Agentic Framework for Safe and Automated Alpha Factor Discovery

arXiv:2604.09601v1 Announce Type: new Abstract: Discovering predictive alpha factors in quantitative finance remains a formidable challenge due to the vast combinatorial search space and inherently lo

safetyarxiv-cs-ai

HuiYanEarth-SAR: A Foundation Model for High-Fidelity and Low-Cost Global Remote Sensing Imagery Generation

arXiv:2604.11444v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery generation is essential for deepening the study of scattering mechanisms, establishing trustworthy electromagneti

Human-AI Interaction Traces as Blackout Poetry: Reframing AI-Supported Writing as Found-Text Creativity

arXiv:2604.09605v1 Announce Type: cross Abstract: LLMs offer new creative possibilities for writers but also raise concerns about authenticity and reader trust, particularly when AI involvement is dis

researcharxiv-cs-ai

Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving

arXiv:2604.11549v1 Announce Type: cross Abstract: In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding

agentsarxiv-cs-lg

Human-like Working Memory Interference in Large Language Models

arXiv:2604.09670v1 Announce Type: cross Abstract: Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity,

researcharxiv-cs-ai

Human vs. Machine Deception: Distinguishing AI-Generated and Human-Written Fake News Using Ensemble Learning

arXiv:2604.09960v1 Announce Type: new Abstract: The rapid adoption of large language models has introduced a new class of AI-generated fake news that coexists with traditional human-written misinforma

HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks

arXiv:2412.17574v3 Announce Type: replace-cross Abstract: Evaluating the nuanced human-centric video understanding capabilities of Multimodal Large Language Models (MLLMs) remains a great challenge, a

HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation

arXiv:2604.09629v1 Announce Type: new Abstract: Humor generation poses a significant challenge for Large Language Models (LLMs), because their standard training objective - predicting the most likely

Hunt Globally: Wide Search AI Agents for Drug Asset Scouting in Investing, Business Development, and Competitive Intelligence

arXiv:2602.15019v3 Announce Type: replace Abstract: Bio-pharmaceutical innovation has shifted: many new drug assets now originate outside the United States and are disclosed primarily via regional, no

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing

model-releasesarxiv-cs-lg

arXiv:2604.10955v1 Announce Type: new Abstract: Hypergraph neural networks (HGNNs) have shown remarkable potential in modeling high-order relationships that naturally arise in many real-world data dom