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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

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High-dimensional Limit of SGD for Diagonal Linear Networks

DGX agent

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

19 May 2026

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

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

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

Agents

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

agentsarxiv-cs-ai

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

researcharxiv-cs-ai

How does feature learning reshape the function space?

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

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

HPC-LLM: Practical Domain Adaptation and Retrieval-Augmented Generation for HPC Support

arXiv:2605.16347v1 Announce Type: new Abstract: Modern scientific research increasingly depends on High-Performance Computing (HPC) infrastructures, yet many researchers face significant operational b

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction

arXiv:2506.03837v2 Announce Type: replace-cross Abstract: The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, resea

Human-Certified Module Repositories for the AI Age

arXiv:2603.02512v4 Announce Type: replace-cross Abstract: Human-Certified Module Repositories (HCMRs) are introduced in this work as a new architectural model for constructing trustworthy software in

researcharxiv-cs-ai

Agents

Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation

arXiv:2605.17426v1 Announce Type: cross Abstract: We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a

agentsarxiv-cs-lg

Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models

arXiv:2602.02039v2 Announce Type: replace Abstract: The agency expected of Agentic Large Language Models goes beyond answering correctly, requiring autonomy to set goals and decide what to explore. We

Hybrid Feature Combinations with CNN for Bangla Fake News Classification

arXiv:2605.17481v1 Announce Type: new Abstract: Nowadays, people in Bangladesh frequently rely on the internet and social media for daily news instead of traditional newspapers. However, the spread of

researcharxiv-cs-cl

Hybrid Quantum-Classical Neural Architecture Search

arXiv:2605.18345v1 Announce Type: cross Abstract: Hybrid quantum-classical neural networks (HQNNs) are emerging as a practical approach for quantum machine learning in the noisy intermediate-scale qua

researcharxiv-cs-lg

Hybrid Quantum-MambaVision: A Quantum-enhanced State Space Model for Calibrated Mixed-type Wafer Defect Detection

arXiv:2605.16404v1 Announce Type: new Abstract: Extracting actionable knowledge from industrial visual data is fundamentally bottlenecked by extreme class imbalance and the prohibitive computational c

applicationsarxiv-cs-cv

HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools

model-releasesarxiv-cs-cl

arXiv:2605.17106v1 Announce Type: new Abstract: Production LLM deployments increasingly maintain heterogeneous model pools spanning order-of-magnitude cost differences. Existing routers make binary st

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL

arXiv:2605.17792v1 Announce Type: new Abstract: Calibrating distributed hydrologic models is a critical bottleneck across operational water resources management - streamflow prediction, reservoir oper

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

arXiv:2605.16527v1 Announce Type: cross Abstract: Hypergraphs model higher-order relations that drive real-world decisions, from drug prescriptions to recommendations. A central structural signal in s

applicationsarxiv-cs-ai

HyperPersona: A Multi-Level Hypergraph Framework for Text-Based Automatic Personality Prediction

arXiv:2605.17355v1 Announce Type: new Abstract: As a modern commodity, language has become a vast repository of socially and psychologically significant traits and concepts, reflecting the ways people

local-aiarxiv-cs-ai

HyperTea: A Hypergraph-based Temporal Enhancement and Alignment Network for Moving Infrared Small Target Detection

arXiv:2508.10678v2 Announce Type: replace Abstract: In practical application scenarios, moving infrared small target detection (MIRSTD) remains highly challenging due to the target's small size, weak

local-aiarxiv-cs-cv

HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone

arXiv:2605.17286v1 Announce Type: new Abstract: While hyperspectral imaging provides rich spatial-spectral information across hundreds of narrow wavelength bands for precise material identification, g

HYVINT: Intensity-Driven Hypergraph Generation with Variational Representations

arXiv:2605.16836v1 Announce Type: cross Abstract: Hypergraphs provide a principled framework for modeling polyadic interactions, with applications in recommendation systems, social networks, and molec

applicationsarxiv-cs-lg

Identifiable Token Correspondence for World Models

arXiv:2605.16457v1 Announce Type: cross Abstract: Transformer-based world models have shown strong performance in visual reinforcement learning, but often suffer from temporal inconsistency in long-ho

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure

arXiv:2605.16682v1 Announce Type: new Abstract: Identifying latent state representations and dynamics is essential when direct modeling in observation space is infeasible, particularly under partial a

researcharxiv-cs-lg

Identifying Latent Actions and Dynamics from Offline Data via Demonstrator Diversity

arXiv:2603.17577v2 Announce Type: replace-cross Abstract: Can latent actions and environment dynamics be recovered from offline trajectories when actions are never observed? We study this question in

IdGlow: Dynamic Identity Modulation for Multi-Subject Generation

arXiv:2603.00607v2 Announce Type: replace-cross Abstract: Multi-subject image generation requires seamlessly harmonizing multiple reference identities within a coherent scene. However, existing method

local-aiarxiv-cs-ai

'I'm Not Mad, Just Focused'': Understanding Human Emotions in Human-Robot Collaboration

arXiv:2605.16816v1 Announce Type: new Abstract: Human-robot collaboration (HRC) can benefit from robots' abilities to interpret human emotional states. However, current emotion recognition (ER) models

safetyarxiv-cs-ro

Image-to-Video Diffusion: From Foundations to Open Frontiers

arXiv:2605.17248v1 Announce Type: new Abstract: Diffusion-based extit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional c

Imaging Hidden Objects with Consumer LiDAR via Motion Induced Sampling

arXiv:2605.17865v1 Announce Type: new Abstract: LiDARs are being increasingly deployed for consumer imaging in handheld, wearable, and robotic applications. These sensors can capture the time-of-fligh

iMiGUE-3K: A Large-Scale Benchmark for Micro-Gesture Analysis with Self-Supervised Learning

model-releasesarxiv-cs-cv

arXiv:2605.17179v1 Announce Type: new Abstract: Emotion understanding is a fundamental challenge in affective computing and artificial intelligence. While existing approaches predominantly focus on fa

Implicit Hierarchical GRPO: Decoupling Tool Invocation from Execution for Tool-Integrated Mathematical Reasoning

arXiv:2605.18500v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly leveraged tool invocation to enhance their reasoning capabilities. However, existing approaches typically

safetyarxiv-cs-cl

Improved Baselines with Representation Autoencoders

arXiv:2605.18324v1 Announce Type: cross Abstract: Representation Autoencoders (RAE) replace traditional VAE with pretrained vision encoders. In this paper, we systematically investigate several design

Improving BM25 Code Retrieval Under Fixed Generic Tokenization: Adaptive q-Log Odds as a Drop-In BM25 Fix

arXiv:2605.18561v1 Announce Type: cross Abstract: In retrieval-augmented coding, failures often begin when the relevant file is absent from the retrieved context. Under frozen generic tokenization, wh

Improving MLLM Training Efficiency via Stage-Aware Sparsity

arXiv:2509.18150v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance across a variety of domains. However, training MLLMs is oft