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arXiv:2604.23350v1 Announce Type: cross Abstract: Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent ch

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Research

Geometric Analysis of Self-Supervised Vision Representations for Semantic Image Retrieval

DGX agent

arXiv:2604.24469v1 Announce Type: cross Abstract: Content-based image retrieval (CBIR) systems enable users to search images based on visual content instead of relying on metadata. The text domain has

researcharxiv-cs-cv

28 Apr 2026

Geometry-Aware Offline-to-Online Learning in Linear Contextual Bandits

arXiv:2604.24016v1 Announce Type: new Abstract: We study offline-to-online learning in linear contextual bandits with biased offline regression data: the offline parameter need not match the online on

Geometry-Conditioned Diffusion for Occlusion-Robust In-Bed Pose Estimation

arXiv:2604.23651v1 Announce Type: new Abstract: Robust in-bed human pose estimation under blanket occlusion remains challenging due to the scarcity of reliable labeled training data for heavily covere

researcharxiv-cs-cv

Geometry Preserving Loss Functions Promote Improved Adaptation of Blackbox Generative Model

arXiv:2604.23888v1 Announce Type: cross Abstract: Adaptation of blackbox generative models has been widely studied recently through the exploration of several methods including generator fine-tuning,

GIFT: Global stabilisation via Intrinsic Fine Tuning

arXiv:2604.23312v1 Announce Type: cross Abstract: Deep reinforcement learning policies achieve strong performance in complex continuous control environments with nonlinear contact forces. However, the

applicationsarxiv-cs-ai

GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval

arXiv:2604.23779v1 Announce Type: cross Abstract: The semantic gap between colloquial user queries and professional legal documents presents a fundamental challenge in Legal Case Retrieval (LCR). Exis

applicationsarxiv-cs-ai

Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation

arXiv:2604.24396v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are frequently undermined by object hallucination--generating content that contradicts visual reality--due to an over-re

GoClick: Lightweight Element Grounding Model for Autonomous GUI Interaction

arXiv:2604.23941v1 Announce Type: new Abstract: Graphical User Interface (GUI) element grounding (precisely locating elements on screenshots based on natural language instructions) is fundamental for

Governing What You Cannot Observe: Adaptive Runtime Governance for Autonomous AI Agents

arXiv:2604.24686v1 Announce Type: new Abstract: Autonomous AI agents can remain fully authorized and still become unsafe as behavior drifts, adversaries adapt, and decision patterns shift without any

safetyarxiv-cs-ai

Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations

arXiv:2511.09749v2 Announce Type: replace Abstract: Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris f

applicationsarxiv-cs-cv

GradMAP: Gradient-Based Multi-Agent Proximal Learning for Grid-Edge Flexibility

arXiv:2604.24549v1 Announce Type: cross Abstract: Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting thr

Grammar-Constrained Refinement of Safety Operational Rules Using Language in the Loop: What Could Go Wrong

arXiv:2604.23523v1 Announce Type: cross Abstract: Safety specifications in cyber-physical systems (CPS) capture the operational conditions the system must satisfy to operate safely within its intended

safetyarxiv-cs-ai

Graph-augmented Segmentation of Complex Shapes in Laser Powder bed Fusion for Enhanced In Situ Inspection

arXiv:2604.24234v1 Announce Type: new Abstract: The technological maturity of in situ inspection and monitoring methods in additive manufacturing is steadily increasing, enabling more efficient and pr

Graph Memory Transformer (GMT)

arXiv:2604.23862v1 Announce Type: cross Abstract: We investigate whether the Feed-Forward Network (FFN) sublayer in a decoder-only transformer can be replaced by an explicit learned memory graph while

GraphPlanner: Graph Memory-Augmented Agentic Routing for Multi-Agent LLMs

model-releasesarxiv-cs-cl

arXiv:2604.23626v1 Announce Type: new Abstract: LLM routing has achieved promising results in integrating the strengths of diverse models while balancing efficiency and performance. However, to suppor

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference

arXiv:2503.10666v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become widely used across various domains spanning search engines, code generation, and text creation. Howev

Green Shielding: A User-Centric Approach Towards Trustworthy AI

arXiv:2604.24700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users p

Tutorials

Gromov-Wasserstein Methods for Multi-View Relational Embedding and Clustering

arXiv:2604.23912v1 Announce Type: new Abstract: Learning low-dimensional representations from multi-view relational data is challenging when underlying geometries differ across views. We propose Bary-

tutorialsarxiv-cs-lg

Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer

arXiv:2604.24062v1 Announce Type: new Abstract: Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and

Group Orthogonal Low-Rank Adaptation for RGB-T Tracking

arXiv:2512.05359v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning has emerged as a promising paradigm in RGB-T tracking, enabling downstream task adaptation by freezing pretrained pa

GS-DOT: Gaussian splatting-based image reconstruction for diffuse optical tomography

arXiv:2604.23675v1 Announce Type: cross Abstract: This work presents GS-DOT, a novel image reconstruction framework based on Gaussian Splatting (GS) for diffuse optical tomography (DOT). Inspired by G

researcharxiv-cs-cv

GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs

arXiv:2604.23366v1 Announce Type: new Abstract: Autonomous multi-agent LLM systems are increasingly deployed to investigate operational incidents and produce structured diagnostic reports. Their trust

GSC-QEMit: A Telemetry-Driven Hierarchical Forecast-and-Bandit Framework for Adaptive Quantum Error Mitigation

arXiv:2604.24551v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) is essential for extracting reliable results from near-term quantum devices, yet practical deployments must balance mit

GTAC: A Generative Transformer for Approximate Circuits

arXiv:2601.19906v2 Announce Type: replace-cross Abstract: Targeting error-tolerant applications, approximate computing relaxes rigid functional equivalence to significantly improve power, performance,

Guided Speculative Inference for Efficient Test-Time Alignment of LLMs

arXiv:2506.04118v3 Announce Type: replace Abstract: We propose Guided Speculative Inference (GSI), a novel algorithm for efficient reward-guided decoding in large language models. GSI combines soft be

safetyarxiv-cs-lg

Guiding Vector Field Generation via Score-based Diffusion Model

arXiv:2604.24487v1 Announce Type: new Abstract: Guiding Vector Fields (GVFs) are a powerful tool for robotic path following. However, classical methods assume smooth, ordered curves and fail when path

researcharxiv-cs-ro

GWT: Scalable Optimizer State Compression for Large Language Model Training

arXiv:2501.07237v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing benchmarks. However, the es

Local Ai

h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network

arXiv:2604.23134v1 Announce Type: new Abstract: Accurate molecular representations are critical for drug discovery, and a central challenge lies in capturing the chemical environment of molecular frag

local-aiarxiv-cs-lg

H-SemiS: Hierarchical Fusion of Semi and Self-Supervised Learning for Knee Osteoarthritis Severity Grading

arXiv:2604.23335v1 Announce Type: new Abstract: Knee osteoarthritis (KOA) is a degenerative joint disease that can lead to chronic pain, reduced mobility, and long-term disability. Automated severity

researcharxiv-cs-cv

HAC: Parameter-Efficient Hyperbolic Adaptation of CLIP for Zero-Shot VQA

arXiv:2604.23665v1 Announce Type: new Abstract: Recent advances in representation learning have shown that hyperbolic geometry can offer a more expressive alternative to the Euclidean embeddings used

HalalBench: A Multilingual OCR Benchmark for Food Packaging Ingredient Extraction

model-releasesarxiv-cs-cl

arXiv:2604.22754v1 Announce Type: cross Abstract: No standardized benchmark exists for evaluating OCR on food packaging, despite its critical role in automated halal food verification. Existing benchm

Hardware

Hallo-Live: Real-Time Streaming Joint Audio-Video Avatar Generation with Asynchronous Dual-Stream and Human-Centric Preference Distillation

arXiv:2604.23632v1 Announce Type: new Abstract: Real-time text-driven joint audio-video avatar generation requires jointly synthesizing portrait video and speech with high fidelity and precise synchro

hardwarearxiv-cs-cv

Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data

arXiv:2604.23606v1 Announce Type: new Abstract: Lattice Hamiltonian systems underpin models across condensed matter, nonlinear optics, and biophysics, yet learning their dynamics from data is obstruct

Hard to See, Hard to Label: Generative and Symbolic Acquisition for Subtle Visual Phenomena

arXiv:2604.22990v1 Announce Type: cross Abstract: Subtle visual anomalies such as hairline cracks, sub-millimeter voids, and low-contrast inclusions are structurally atypical yet visually ambiguous, m

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization

arXiv:2511.08425v3 Announce Type: replace Abstract: Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distri

researcharxiv-cs-lg

Hardware-Efficient FPGA Implementation of Sigmoid Function Using Mixed-Radix Hyperbolic Rotation CORDIC

arXiv:2604.23547v1 Announce Type: cross Abstract: Efficient hardware implementation of nonlinear activation functions is a crucial task in deploying artificial neural networks on resource-constrained

Hardware-Efficient Softmax and Layer Normalization with Guaranteed Normalization for Edge Devices

arXiv:2604.23647v1 Announce Type: cross Abstract: In Transformer models, non-GEMM (non-General Matrix Multiplication) operations -- especially Softmax and Layer Normalization (LayerNorm) -- often domi

researcharxiv-cs-lg

HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction

arXiv:2604.23115v1 Announce Type: new Abstract: Accurate prediction of drug-target binding affinity accelerates drug discovery by prioritizing compounds for experimental validation. Current methods fa

HeadRouter: Dynamic Head-Weight Routing for Task-Adaptive Audio Token Pruning in Large Audio Language Models

arXiv:2604.23717v1 Announce Type: cross Abstract: Recent large audio language models (LALMs) demonstrate remarkable capabilities in processing extended multi-modal sequences, yet incur high inference

researcharxiv-cs-cl

Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs

arXiv:2512.16378v4 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly proce

HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness

arXiv:2603.17573v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative

applicationsarxiv-cs-lg

Local Ai

Hidden States Know Where Reasoning Diverges: Credit Assignment via Span-Level Wasserstein Distance

arXiv:2604.23318v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) performs coarse-grained credit assignment in reinforcement learning with verifiable rewards (RLVR) by assignin

local-aiarxiv-cs-cl

Hierarchical Behaviour Spaces

arXiv:2604.24558v1 Announce Type: new Abstract: Recent work in hierarchical reinforcement learning has shown success in scaling to billions of timesteps when learning over a set of predefined option r

Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis

arXiv:2604.23982v1 Announce Type: new Abstract: Digital pathology has fundamentally altered diagnostic workflows by enabling the computational analysis of gigapixel Whole Slide Images (WSIs), yet effe

safetyarxiv-cs-cv

Hierarchical RL-MPC Control for Dynamic Wake Steering in Wind Farms

arXiv:2604.22797v1 Announce Type: cross Abstract: Wind farm wake steering optimization is challenging due to complex flow physics and changing conditions. This paper presents a hierarchical framework

safetyarxiv-cs-lg

Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis

arXiv:2604.23375v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have become increasingly difficult to deploy in resource-constrained environments due to their large memory and com

High-accuracy sampling for diffusion models and log-concave distributions

arXiv:2602.01338v2 Announce Type: replace Abstract: We present algorithms for diffusion model sampling which obtain elta-error in polylog(1/elta) steps, given access to widetilde O(elta)-accurate scor

researcharxiv-cs-lg