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GraphMind: From Operational Traces to Self-Evolving Workflow Automation

arXiv:2605.17617v1 Announce Type: new Abstract: Complex operational workflows coordinating personnel, tools, and information are central to enterprise operations, yet end-to-end automation remains cha

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GraphMind: Theorem Selection and Conclusion Generation Framework with Dynamic GNN for LLM Reasoning

DGX agent

arXiv:2511.19078v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, including multi-step

researcharxiv-cs-ai

19 May 2026

GRASP: Graph Agentic Search over Propositions for Multi-hop Question Answering

arXiv:2605.16598v1 Announce Type: cross Abstract: Agentic retrieval improves multi-hop question answering by giving language models autonomy to iteratively gather evidence. Recent work augments these

GraSP-VL: Length as a Semantic Granularity Interface for Vision-Language Representations

arXiv:2605.17727v1 Announce Type: new Abstract: Frozen vision-language embeddings contain signals at multiple semantic resolutions, from object identity to attributes, relations, and full-caption mean

GraViti: Graph-Level Variational Autoencoders with Relaxed Permutation Invariance

arXiv:2605.16668v1 Announce Type: cross Abstract: We introduce GraViti, a transformer-based graph-level variational autoencoder that maps entire graphs to compact latent vectors. This design produces

GRID: Graph Representation of Intelligence Data for Security Text Knowledge Graph Construction

arXiv:2605.16714v1 Announce Type: new Abstract: Security knowledge graphs can provide computable external memory for security agents, but constructing them from long-form cyber threat intelligence (CT

Hardware

Guard: Scalable Straggler Detection and Node Health Management for Large-Scale Training

arXiv:2605.17879v1 Announce Type: cross Abstract: Training frontier-scale foundation models involves coordinating tens of thousands of GPUs over multi-month runs, where even minor performance degradat

hardwarearxiv-cs-ai

Tutorials

GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries

arXiv:2411.03936v2 Announce Type: replace Abstract: Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires emplo

tutorialsarxiv-cs-lg

Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robots

arXiv:2507.16481v3 Announce Type: replace Abstract: Jumping poses a significant challenge for quadruped robots, despite being crucial for many operational scenarios. While optimisation methods exist f

safetyarxiv-cs-ro

GUT-IS: A Data-Driven Approach to Integrating Constructs and Their Relations in Information Systems

arXiv:2605.18567v1 Announce Type: new Abstract: Structural equation modeling is widely used in IS research. However, inconsistent construct definitions impede the cumulative development of knowledge.

researcharxiv-cs-cl

GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games

arXiv:2508.08501v3 Announce Type: replace Abstract: We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built

HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction

arXiv:2605.16873v1 Announce Type: new Abstract: Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at

HalluScore: Large Language Model Hallucination Question Answering Benchmark

model-releasesarxiv-cs-cl

arXiv:2605.17007v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress in natural language generation, but remain susceptible to hallucination. In response to g

Haptic Rendering of Fractional-Order Viscoelasticity: Passivity and Rendering Fidelity

arXiv:2605.16389v1 Announce Type: cross Abstract: Haptic rendering of viscoelastic materials that exhibit creep and stress relaxation is crucial for many applications, such as medical training with re

Applications

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects

arXiv:2605.16966v1 Announce Type: new Abstract: Solving inverse partial differential equation (PDE) problems is a fundamental topic in scientific research due to its broad significance across a wide r

applicationsarxiv-cs-ai

Harnessing LLM Agents with Skill Programs

arXiv:2605.17734v1 Announce Type: new Abstract: Equipping LLM agents with reusable skills derived from past experience has become a popular and successful approach for tackling complex and long-horizo

Hardware

Hawkeye: Reproducing GPU-Level Non-Determinism

arXiv:2603.20421v2 Announce Type: replace-cross Abstract: We present Hawkeye, a system for analyzing and reproducing GPU-level arithmetic operations. Using our framework, anyone can re-execute on a CP

hardwarearxiv-cs-lg

HCLM: A Hierarchical Framework for Cooperative Loco-Manipulation with Dual Quadrupeds

arXiv:2605.17300v1 Announce Type: new Abstract: We introduce HCLM, a hierarchical framework for general-purpose cooperative loco-manipulation with dual quadrupedal systems. Coordinating multi-robot co

safetyarxiv-cs-ro

HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference

arXiv:2506.23287v3 Announce Type: replace Abstract: In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological proc

researcharxiv-cs-lg

HEED: Density-Weighted Residual Alignment for Hybrid Vision-Language Model Distillation

model-releasesarxiv-cs-cl

arXiv:2605.17093v1 Announce Type: cross Abstract: Distilling vision-language models into faster hybrid architectures, such as 3:1 Mamba-2/attention mixes, is now standard practice for making inference

Helpful to a Fault: Measuring Illicit Assistance in Multi-Turn, Multilingual LLM Agents

arXiv:2602.16346v3 Announce Type: replace Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to ca

safetyarxiv-cs-cl

Helping Customers in Distress: An LLM-powered Agent that Converses, Probes, and Routes

arXiv:2605.16268v1 Announce Type: cross Abstract: Banks receive millions of reports of fraud, scams, and disputed transactions every year, making it challenging to accurately direct customers to the a

Local Ai

Herding CATs: ALARA for Agent Harness Engineering in Portable Composable Multi-Agent Teams

arXiv:2603.20380v2 Announce Type: replace-cross Abstract: Industry practitioners and academic researchers regularly use multi-agent systems to accelerate their work, but the applications through which

local-aiarxiv-cs-ai

Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning

arXiv:2605.17393v1 Announce Type: new Abstract: Coordination graphs are a central abstraction in cooperative multi-agent reinforcement learning (MARL), yet existing sparse-graph learners lack a theore

Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach

arXiv:2605.18437v1 Announce Type: new Abstract: Vehicular edge computing (VEC) enables latency-sensitive vehicular applications by offloading computation-intensive tasks to nearby edge servers. Howeve

safetyarxiv-cs-lg

HexagonalWarriorMamba: Superior Threshold-Dependent Multi-label Classification of 12-Lead ECG Cardiac Abnormalities

arXiv:2605.17875v1 Announce Type: new Abstract: The accurate automated diagnosis of cardiac abnormalities from 12-lead electrocardiograms (ECGs) is critical for managing cardiovascular disease. Howeve

Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction

arXiv:2605.16442v1 Announce Type: cross Abstract: Long-horizon vessel trajectory forecasting under real ocean conditions is critical for collision avoidance, traffic management, and route planning. Ho

Local Ai

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing

arXiv:2605.17294v1 Announce Type: new Abstract: High-resolution image editing is essential for professional and creative applications, yet existing multimodal diffusion-based editors remain computatio

local-aiarxiv-cs-cv

High-dimensional Limit of SGD for Diagonal Linear Networks

arXiv:2605.17177v1 Announce Type: cross Abstract: Understanding the behavior of stochastic gradient methods is a central problem in modern machine learning. Recent work has highlighted diagonal linear

researcharxiv-cs-lg

High-dimensional ridge regression with random features for non-identically distributed data with a variance profile

model-releasesarxiv-cs-lg

arXiv:2504.03035v2 Announce Type: replace-cross Abstract: Random feature ridge regression is often analyzed in the high-dimensional regime under the homogeneous sampling model x_i=Sigma^{1/2}x_i', whe

Tutorials

High-Resolution Reference Image Assisted Volumetric Super-Resolution of Cardiac Diffusion Weighted Imaging

arXiv:2310.20389v2 Announce Type: replace-cross Abstract: Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human hear

tutorialsarxiv-cs-cv

Applications

HighSync: High-Quality Lip Synchronization via Latent Diffusion Models

arXiv:2605.16918v1 Announce Type: new Abstract: We present HighSync, an end-to-end diffusion-based framework for high-fidelity lip synchronization that generates photorealistic talking-face videos ali

applicationsarxiv-cs-cv

Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning

arXiv:2605.16385v1 Announce Type: cross Abstract: Geometric problem solving, as a typical multimodal reasoning problem, has attracted much attention and made great progress recently, however most of w

HINT-SD: Targeted Hindsight Self-Distillation for Long-Horizon Agents

arXiv:2605.17873v1 Announce Type: cross Abstract: Training long-horizon LLM agents with reinforcement learning is challenging because sparse outcome rewards reveal whether a task succeeds, but not whi

Historical Knowledge Graphs for Global Maritime Estimated Time of Arrival

arXiv:2605.18408v1 Announce Type: new Abstract: Accurate vessel estimated-time-of-arrival forecasts are critical for port operations and decarbonization, yet global-scale travel-time prediction remain

HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos

arXiv:2605.17543v1 Announce Type: new Abstract: Video outpainting generates plausible visual content beyond the original spatial extent of a video, playing a key role in adapting videos to diverse dis

Homoglyph-based Adversarial Perturbation of Introductory Computer Science Theory Problems

arXiv:2605.16286v1 Announce Type: cross Abstract: Different AI tools such as ChatGPT, Gemini, and Claude are becoming very popular. Although they are helpful for many day-to-day tasks, they can be use

Tutorials

How Class Ontology and Data Scale Affect Audio Transfer Learning

arXiv:2603.25476v2 Announce Type: replace Abstract: Transfer learning is a crucial concept within deep learning that allows artificial neural networks to benefit from a large pre-training data basis w

tutorialsarxiv-cs-lg

How Do Electrocardiogram Models Scale?

arXiv:2605.17276v1 Announce Type: cross Abstract: While scaling laws have established a fundamental framework for foundation models in natural language processing, their applicability to electrocardio

How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study

arXiv:2605.16953v1 Announce Type: new Abstract: While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled b

How does feature learning reshape the function space?

model-releasesarxiv-cs-lg

arXiv:2605.17718v1 Announce Type: cross Abstract: Feature learning is widely regarded as the key mechanism distinguishing neural networks from fixed-kernel methods, yet its impact on the induced funct

How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning

arXiv:2605.16591v1 Announce Type: cross Abstract: In-context learning (ICL) excels at new tasks from minimal examples, yet we still lack a mechanistic explanation of how few-shot prompts shape a model

How Good LLMs Are at Answering Bangla Medical Visual Questions? Dataset and Benchmarking

model-releasesarxiv-cs-cl

arXiv:2605.18111v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) and Large Vision Language Models (LVLMs) have enabled general-purpose systems to demonstrate promisi

How Loud Rumbles Hit Newsstands: A Data Analysis of Coverage and Spatial Bias in German News about Landslides Around the World

arXiv:2605.18105v1 Announce Type: new Abstract: Landslides often hit newsstands due to their destructive and potentially fatal effects. News are a valuable source of information for creating or enrich

safetyarxiv-cs-cl

Local Ai

How Many Visual Tokens Do Multimodal Language Models Need? Scaling Visual Token Pruning with F^3A

arXiv:2605.16359v1 Announce Type: cross Abstract: Vision-language models improve perception by feeding increasingly long visual token sequences into language backbones, but the resulting inference cos

local-aiarxiv-cs-ai

How Off-Policy Can GRPO Be? Mu-GRPO for Efficient LLM Reinforcement Learning

arXiv:2605.17570v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has been a key driver of recent progress in reinforcement learning with verifiable rewards (RLVR) for large

safetyarxiv-cs-cl

How to Instruct Your Robot: Dense Language Annotations Power Robot Policy Learning

arXiv:2605.17077v1 Announce Type: cross Abstract: Scaling robot policy learning is bottlenecked by the cost of collecting demonstrations, while language annotations for existing demonstrations are com

How Wrong Can Your Counterfactual Be? Quantifying Confounding Bias for Continuous Treatments without a Control Group

arXiv:2603.07438v2 Announce Type: replace Abstract: Stress testing poses a causal question: how would portfolio credit losses change if the macroeconomy followed an adverse counterfactual path? Yet st