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arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

tutorialsarxiv-cs-cv

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Generating Attribution Reports for Manipulated Facial Images: A Dataset and Baseline

DGX agent

arXiv:2412.19685v2 Announce Type: replace-cross Abstract: Existing facial forgery detection methods typically focus on binary classification or pixel-level localization, providing little semantic insi

model-releasesarxiv-cs-ai

10 Apr 2026

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting

arXiv:2604.07928v1 Announce Type: new Abstract: While AI-based numerical weather prediction (NWP) enables rapid forecasting, generating high-resolution outputs remains computationally demanding due to

Generative Phomosaic with Structure-Aligned and Personalized Diffusion

arXiv:2604.06989v1 Announce Type: cross Abstract: We present the first generative approach to photomosaic creation. Traditional photomosaic methods rely on a large number of tile images and color-base

researcharxiv-cs-ai

GenLCA: 3D Diffusion for Full-Body Avatars from In-the-Wild Videos

arXiv:2604.07273v2 Announce Type: replace Abstract: We present GenLCA, a diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs. The ge

applicationsarxiv-cs-cv

Geometric Properties of the Voronoi Tessellation in Latent Semantic Manifolds of Large Language Models

arXiv:2604.06767v1 Announce Type: new Abstract: Language models operate on discrete tokens but compute in continuous vector spaces, inducing a Voronoi tessellation over the representation manifold. We

safetyarxiv-cs-lg

GIFT: Group-Relative Implicit Fine-Tuning Integrates GRPO with DPO and UNA

arXiv:2510.23868v4 Announce Type: replace Abstract: This paper proposes extit{Group-relative Implicit Fine-Tuning (GIFT)}, a reinforcement learning framework for aligning large language models (LLMs

safetyarxiv-cs-lg

Local Ai

Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria

arXiv:2604.06018v2 Announce Type: replace-cross Abstract: This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study. The

local-aiarxiv-cs-ai

Governed Capability Evolution for Embodied Agents: Safe Upgrade, Compatibility Checking, and Runtime Rollback for Embodied Capability Modules

arXiv:2604.08059v1 Announce Type: new Abstract: Embodied agents are increasingly expected to improve over time by updating their executable capabilities rather than rewriting the agent itself. Prior w

safetyarxiv-cs-ro

Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030

arXiv:2604.06215v1 Announce Type: cross Abstract: The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical

safetyarxiv-cs-ai

Graph Neural Networks for Misinformation Detection: Performance-Efficiency Trade-offs

arXiv:2604.08131v1 Announce Type: new Abstract: The rapid spread of online misinformation has led to increasingly complex detection models, including large language models and hybrid architectures. Ho

Hardware

Graph Neural ODE Digital Twins for Control-Oriented Reactor Thermal-Hydraulic Forecasting Under Partial Observability

arXiv:2604.07292v1 Announce Type: new Abstract: Real-time supervisory control of advanced reactors requires accurate forecasting of plant-wide thermal-hydraulic states, including locations where physi

hardwarearxiv-cs-lg

GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records

arXiv:2604.06684v1 Announce Type: new Abstract: Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in modern healthcare. While in-context learning (ICL) offer

applicationsarxiv-cs-lg

Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations

arXiv:2604.07517v1 Announce Type: new Abstract: Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vas

safetyarxiv-cs-ro

GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning

arXiv:2604.07808v1 Announce Type: new Abstract: Full-parameter fine-tuning of large language models is constrained by substantial GPU memory requirements. Low-rank adaptation methods mitigate this cha

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis

arXiv:2604.08301v1 Announce Type: new Abstract: The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently,

GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant

arXiv:2603.01059v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have enabled increasingly capable chatbots. However, most existing systems focus on single-user sett

GS-Surrogate: Deformable Gaussian Splatting for Parameter Space Exploration of Ensemble Simulations

model-releasesarxiv-cs-ai

arXiv:2604.06358v1 Announce Type: cross Abstract: Exploring ensemble simulations is increasingly important across many scientific domains. However, supporting flexible post-hoc exploration remains cha

Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

arXiv:2604.08046v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current res

researcharxiv-cs-cl

Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs

arXiv:2604.07655v1 Announce Type: cross Abstract: Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yield

Guiding a Diffusion Model by Swapping Its Tokens

arXiv:2604.08048v1 Announce Type: new Abstract: Classifier-Free Guidance (CFG) is a widely used inference-time technique to boost the image quality of diffusion models. Yet, its reliance on text condi

safetyarxiv-cs-cv

Hallucination as output-boundary misclassification: a composite abstention architecture for language models

arXiv:2604.06195v1 Announce Type: cross Abstract: Large language models often produce unsupported claims. We frame this as a misclassification error at the output boundary, where internally generated

researcharxiv-cs-ai

Local Ai

Hallucination Detection and Evaluation of Large Language Model

arXiv:2512.22416v2 Announce Type: replace Abstract: Hallucinations in Large Language Models (LLMs) pose a significant challenge, generating misleading or unverifiable content that undermines trust and

local-aiarxiv-cs-cl

Harf-Speech: A Clinically Aligned Framework for Arabic Phoneme-Level Speech Assessment

model-releasesarxiv-cs-ai

arXiv:2604.06191v1 Announce Type: cross Abstract: Automated phoneme-level pronunciation assessment is vital for scalable speech therapy and language learning, yet validated tools for Arabic remain sca

Harnessing Embodied Agents: Runtime Governance for Policy-Constrained Execution

arXiv:2604.07833v1 Announce Type: new Abstract: Embodied agents are evolving from passive reasoning systems into active executors that interact with tools, robots, and physical environments. Once gran

safetyarxiv-cs-ro

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization

arXiv:2604.06285v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual inform

safetyarxiv-cs-ai

Hardware

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models

arXiv:2604.07812v1 Announce Type: new Abstract: In multimodal large language models (MLLMs), the surge of visual tokens significantly increases the inference time and computational overhead, making th

hardwarearxiv-cs-cv

HCRE: LLM-based Hierarchical Classification for Cross-Document Relation Extraction with a Prediction-then-Verification Strategy

arXiv:2604.07937v1 Announce Type: new Abstract: Cross-document relation extraction (RE) aims to identify relations between the head and tail entities located in different documents. Existing approache

researcharxiv-cs-cl

HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation

arXiv:2604.07993v1 Announce Type: new Abstract: Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts larg

applicationsarxiv-cs-ro

HiCI: Hierarchical Construction-Integration for Long-Context Attention

arXiv:2603.20843v2 Announce Type: replace Abstract: Long-context language modeling is commonly framed as a scalability challenge of token-level attention, yet local-to-global information structuring r

Hierarchical Feature Learning for Medical Point Clouds via State Space Model

arXiv:2504.13015v3 Announce Type: replace Abstract: Deep learning-based point cloud modeling has been widely investigated as an indispensable component of general shape analysis. Recently, transformer

HiF-VLA: Hindsight, Insight and Foresight through Motion Representation for Vision-Language-Action Models

arXiv:2512.09928v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently enabled robotic manipulation by grounding visual and linguistic cues into actions. However, most V

applicationsarxiv-cs-ro

High-Precision Estimation of the State-Space Complexity of Shogi via the Monte Carlo Method

arXiv:2604.06189v1 Announce Type: new Abstract: Determining the state-space complexity of the game of Shogi (Japanese Chess) has been a challenging problem, with previous combinatorial estimates leavi

applicationsarxiv-cs-ai

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues

model-releasesarxiv-cs-ai

arXiv:2604.06845v1 Announce Type: cross Abstract: Long-term memory is critical for dialogue systems that support continuous, sustainable, and personalized interactions. However, existing methods rely

HistDiT: A Structure-Aware Latent Conditional Diffusion Model for High-Fidelity Virtual Staining in Histopathology

model-releasesarxiv-cs-cv

arXiv:2604.08305v1 Announce Type: cross Abstract: Immunohistochemistry (IHC) is essential for assessing specific immune biomarkers like Human Epidermal growth-factor Receptor 2 (HER2) in breast cancer

Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels

model-releasesarxiv-cs-lg

arXiv:2604.06614v1 Announce Type: cross Abstract: Prompt learning has gained significant attention as a parameter-efficient approach for adapting large pre-trained vision-language models to downstream

Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Colored Point Clouds

arXiv:2411.07799v3 Announce Type: replace Abstract: Accurate and consistent fruit monitoring over time is a key step toward automated agricultural production systems. However, this task is inherently

applicationsarxiv-cs-cv

HOTFLoc++: End-to-End Hierarchical LiDAR Place Recognition, Re-Ranking, and 6-DoF Metric Localisation in Forests

arXiv:2511.09170v2 Announce Type: replace Abstract: This article presents HOTFLoc++, an end-to-end hierarchical framework for LiDAR place recognition, re-ranking, and 6-DoF metric localisation in fore

How Does Machine Learning Manage Complexity?

arXiv:2604.07233v1 Announce Type: new Abstract: We provide a computational complexity lens to understand the power of machine learning models, particularly their ability to model complex systems. Mach

researcharxiv-cs-lg

How Independent are Large Language Models? A Statistical Framework for Auditing Behavioral Entanglement and Reweighting Verifier Ensembles

arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra

Agents

How Much LLM Does a Self-Revising Agent Actually Need?

arXiv:2604.07236v2 Announce Type: new Abstract: Recent LLM-based agents often place world modeling, planning, and reflection inside a single language model loop. This can produce capable behavior, but

agentsarxiv-cs-ai

How Psychological Learning Paradigms Shaped and Constrained Artificial Intelligence

arXiv:2603.18203v3 Announce Type: replace Abstract: Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel config

How to Evaluate Speech Translation with Source-Aware Neural MT Metrics

arXiv:2511.03295v3 Announce Type: replace-cross Abstract: Automatic evaluation of ST systems is typically performed by comparing translation hypotheses with one or more reference translations. While e

safetyarxiv-cs-ai

Tutorials

How to sketch a learning algorithm

arXiv:2604.07328v1 Announce Type: new Abstract: How does the choice of training data influence an AI model? This question is of central importance to interpretability, privacy, and basic science. At i

tutorialsarxiv-cs-lg

Local Ai

HQF-Net: A Hybrid Quantum-Classical Multi-Scale Fusion Network for Remote Sensing Image Segmentation

arXiv:2604.06715v1 Announce Type: cross Abstract: Remote sensing semantic segmentation requires models that can jointly capture fine spatial details and high-level semantic context across complex scen

local-aiarxiv-cs-ai

HST-HGN: Heterogeneous Spatial-Temporal Hypergraph Networks with Bidirectional State Space Models for Global Fatigue Assessment

arXiv:2604.08435v1 Announce Type: new Abstract: It remains challenging to assess driver fatigue from untrimmed videos under constrained computational budgets, due to the difficulty of modeling long-ra

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s

HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents

model-releasesarxiv-cs-cv

arXiv:2604.07430v1 Announce Type: new Abstract: We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Visi