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FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting

arXiv:2605.00177v1 Announce Type: cross Abstract: We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics

applicationsarxiv-cs-cv

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FinSafetyBench: Evaluating LLM Safety in Real-World Financial Scenarios

DGX agent

arXiv:2605.00706v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied in financial scenarios. However, they may produce harmful outputs, including facilitating illegal

model-releasesarxiv-cs-cl

4 May 2026

Flow matching for Sentinel-2 super-resolution: implementation, application, and implications

arXiv:2605.00367v1 Announce Type: new Abstract: Developing robust techniques for super-resolution of satellite imagery involves navigating commonly observed trade-offs between spectral fidelity and pe

FollowTable: A Benchmark for Instruction-Following Table Retrieval

arXiv:2605.00400v1 Announce Type: cross Abstract: Table Retrieval (TR) has traditionally been formulated as an ad-hoc retrieval problem, where relevance is primarily determined by topical semantic sim

Foresight Arena: An On-Chain Benchmark for Evaluating AI Forecasting Agents

arXiv:2605.00420v1 Announce Type: cross Abstract: Evaluating the true forecasting ability of AI agents requires environments resistant to overfitting, free from centralized trust, and grounded in ince

Foundation AI Models for Aerosol Optical Depth Estimation from PACE Satellite Data

arXiv:2605.00678v1 Announce Type: new Abstract: Aerosol Optical Depth (AOD) retrieval is essential for Earth observation, supporting applications from air quality monitoring to climate studies. Conven

safetyarxiv-cs-cv

Foundation Models for Discovery and Exploration in Chemical Space

arXiv:2510.18900v2 Announce Type: replace-cross Abstract: Accurate prediction of atomistic, thermodynamic, and kinetic properties from molecular structures underpins materials innovation. Existing com

Free Energy Surface Sampling via Reduced Flow Matching

arXiv:2605.00337v1 Announce Type: new Abstract: Sampling the free energy surface, namely, the distribution of collective variables (CVs), is a crucial problem in statistical physics, as it underpins a

FreeRet: MLLMs as Training-Free Retrievers

arXiv:2509.24621v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are emerging as versatile foundations for mixed-modality retrieval. Yet, they often require heavy post-hoc

safetyarxiv-cs-cv

From Backward Spreading to Forward Replay: Revisiting Target Construction in LLM Parameter Editing

arXiv:2605.00358v1 Announce Type: new Abstract: LLM parameter editing methods commonly rely on computing an ideal target hidden-state at a target layer (referred as anchor point) and distributing the

Local Ai

From Birdsong to Rumbles: Classifying Elephant Calls with Out-of-Species Embeddings

arXiv:2605.00225v1 Announce Type: cross Abstract: We show that pretrained acoustic embeddings classify elephant vocalisations at a level approaching that of end-to-end supervised neural networks, with

local-aiarxiv-cs-lg

From Images2Mesh: A 3D Surface Reconstruction Pipeline for Non-Cooperative Space Objects

model-releasesarxiv-cs-cv

arXiv:2605.00147v1 Announce Type: new Abstract: On-orbit inspection imagery is crucial as it enables characterization of non-cooperative resident space objects, providing the geometry and structural c

From Local to Global to Mechanistic: An iERF-Centered Unified Framework for Interpreting Vision Models

arXiv:2605.00474v1 Announce Type: new Abstract: Modern vision models achieve remarkable accuracy, but explaining where evidence arises, what the model encodes, and how internal computations assemble t

From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting

arXiv:2605.00645v1 Announce Type: new Abstract: Clinical time-series forecasting is increasingly studied for decision support, yet standard aggregate metrics can obscure whether a model is actually us

GAFSV-Net: A Vision Framework for Online Signature Verification

arXiv:2605.00120v1 Announce Type: new Abstract: Online signature verification (OSV) requires distinguishing skilled forgeries from genuine samples under high intra-class variability and with very few

Local Ai

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

arXiv:2603.02727v4 Announce Type: replace Abstract: Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers

local-aiarxiv-cs-cv

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables

arXiv:2603.08032v2 Announce Type: replace Abstract: Exogenous variables offer valuable supplementary information for predicting future endogenous variables. Forecasting with exogenous variables needs

GD4: Graph-based Discrete Denoising Diffusion for MIMO Detection

arXiv:2605.00423v1 Announce Type: new Abstract: In wireless communications, recovering the optimal solution to the multiple-input multiple-output (MIMO) detection problem is NP-hard. Obtaining high-qu

Generating Statistical Charts with Validation-Driven LLM Workflows

arXiv:2605.00800v1 Announce Type: new Abstract: Generating diverse, readable statistical charts from tabular data remains challenging for LLMs, as many failures become apparent after rendering and are

Generative Modeling under Non-Monotone MAR Missingness via Approximate Wasserstein Gradient Flows

arXiv:2604.04567v2 Announce Type: replace-cross Abstract: The prevalence of missing values in data science poses a substantial risk to any further analyses. Despite a wealth of research, principled no

Geometric analysis of attractor boundaries and storage capacity limits in kernel Hopfield networks

arXiv:2605.00366v1 Announce Type: cross Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit strong storage capabilities, but the dynamical and geometric mech

GMGaze: MoE-Based Context-Aware Gaze Estimation with CLIP and Multiscale Transformer

arXiv:2605.00799v1 Announce Type: new Abstract: Gaze estimation methods commonly use facial appearances to predict the direction of a person gaze. However, previous studies show three major challenges

GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space

arXiv:2605.00498v1 Announce Type: new Abstract: Recent advances in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made it standard practice to reconstruct 3D scenes from multi-vie

applicationsarxiv-cs-cv

Gradient Regularized Newton Boosting Trees with Global Convergence

arXiv:2605.00581v1 Announce Type: cross Abstract: Gradient Boosting Decision Trees (GBDTs) dominate tabular machine learning, with modern implementations like XGBoost, LightGBM, and CatBoost being bas

Graph Concept Bottleneck Models

arXiv:2508.14255v2 Announce Type: replace Abstract: Concept Bottleneck Models (CBMs) provide explicit interpretations for deep neural networks through concepts and allow intervention with concepts to

Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey

arXiv:2411.17429v2 Announce Type: replace Abstract: Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challeng

Agents

Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration

arXiv:2605.00370v1 Announce Type: new Abstract: Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effe

agentsarxiv-cs-lg

H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations

arXiv:2605.00631v1 Announce Type: new Abstract: We present H-RAG, our submission to SemEval-2026 Task 8 (MTRAGEval), addressing both Task A (Retrieval) and Task C (Generation with Retrieved Passages).

researcharxiv-cs-cl

Agents

Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation

arXiv:2605.00529v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models with external knowledge, and tree-based RAG organizes documents into hierarchical in

agentsarxiv-cs-lg

High-Probability Convergence in Decentralized Stochastic Optimization with Gradient Tracking

arXiv:2605.00281v1 Announce Type: new Abstract: We study high-probability (HP) convergence guarantees in decentralized stochastic optimization, where multiple agents collaborate to jointly train a mod

High-Speed Vision Improves Zero-Shot Semantic Understanding of Human Actions

arXiv:2605.00496v1 Announce Type: new Abstract: Understanding human actions from visual observations is essential for human--robot interaction, particularly when semantic interpretation of unfamiliar

How Frontier LLMs Adapt to Neurodivergence Context: A Measurement Framework for Surface vs. Structural Change in System-Prompted Responses

arXiv:2605.00113v1 Announce Type: new Abstract: We examine if frontier chat-based large language models (LLMs) adjust their outputs based on neurodivergence (ND) context in system prompts and describe

How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework

arXiv:2605.00269v1 Announce Type: new Abstract: Recent white-box OOD detection methods for LLMs -- including CED, RAUQ, and WildGuard confidence scores -- appear effective, but we show they are struct

safetyarxiv-cs-cl

How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks

model-releasesarxiv-cs-cv

arXiv:2507.01955v3 Announce Type: replace Abstract: Multimodal foundation models (MFMs), such as GPT-4o, have recently made remarkable progress. However, their detailed visual understanding beyond que

Human-in-the-Loop Meta Bayesian Optimization for Fusion Energy and Scientific Applications

arXiv:2605.00068v1 Announce Type: new Abstract: Inertial Confinement Fusion (ICF) holds transformative promise for sustainable, near-limitless clean energy, yet remains constrained by prohibitively hi

HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs

arXiv:2605.00820v1 Announce Type: cross Abstract: We introduce HyCOP, a modular framework that learns parametric PDE solution operators by composing simple modules (advection, diffusion, learned closu

safetyarxiv-cs-lg

Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices

arXiv:2605.00351v1 Announce Type: new Abstract: Root cause localization in cloud native microservice systems requires modeling complex service dependencies, irregular temporal dynamics, and heterogene

Local Ai

Hyperspherical Forward-Forward with Prototypical Representations

arXiv:2605.00082v1 Announce Type: new Abstract: The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a co

local-aiarxiv-cs-lg

IdentiFace: Multi-Modal Iterative Diffusion Framework for Identifiable Suspect Face Generation in Crime Investigations

arXiv:2605.00526v1 Announce Type: new Abstract: Suspect face generation remains a technical challenge in crime investigations. Traditional sketch-drawing workflows suffer from low efficiency and quali

applicationsarxiv-cs-cv

Image Score: Learning and Evaluating Human Preferences for Mercari Search

arXiv:2408.11349v2 Announce Type: replace Abstract: Mercari is the largest C2C e-commerce marketplace in Japan, having more than 20 million active monthly users. Search being the fundamental way to di

Impact of Task Phrasing on Presumptions in Large Language Models

arXiv:2605.00436v1 Announce Type: new Abstract: Concerns with the safety and reliability of applying large-language models (LLMs) in unpredictable real-world applications motivate this study, which ex

safetyarxiv-cs-cl

Incomplete Data, Complete Dynamics: A Diffusion Approach

arXiv:2509.20098v2 Announce Type: replace Abstract: Learning physical dynamics from data is a fundamental challenge in machine learning and scientific modeling. Real-world observational data are inher

Information-geometric adaptive sampling for graph diffusion

arXiv:2605.00250v1 Announce Type: cross Abstract: Standard diffusion models for graph generation typically rely on uniform time-stepping, an approach that overlooks the non-homogeneous dynamics of dis

Information-Theoretic Generalization Bounds for Stochastic Gradient Descent with Predictable Virtual Noise

arXiv:2605.00064v1 Announce Type: new Abstract: Information-theoretic generalization bounds analyze stochastic optimization by relating expected generalization error to the mutual information between

InpaintSLat: Inpainting Structured 3D Latents via Initial Noise Optimization

arXiv:2605.00664v1 Announce Type: new Abstract: We present a training-free approach for controllable 3D inpainting based on initial noise optimization. In the structured 3D latent diffusion framework,

safetyarxiv-cs-cv

Instance-Aware Pseudo-Labeling and Class-Focused Contrastive Learning for Weakly Supervised Domain Adaptive Segmentation of Electron Microscopy

arXiv:2510.16450v2 Announce Type: replace Abstract: Annotation-efficient segmentation of the numerous mitochondria instances from various electron microscopy (EM) images is highly valuable for biologi

Intelligent Elastic Feature Fading: Enabling Model Retrain-Free Feature Efficiency Rollouts at Scale

arXiv:2605.00324v1 Announce Type: cross Abstract: Large-scale ranking systems depend on thousands of features derived from user behavior across multiple time horizons. Typically requires model retrain

safetyarxiv-cs-lg

InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information

arXiv:2508.07630v2 Announce Type: replace Abstract: We introduce InterChart, a diagnostic benchmark that evaluates how well vision-language models (VLMs) reason across multiple related charts, a task