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Unveiling High-Probability Generalization in Decentralized SGD

arXiv:2605.10205v1 Announce Type: new Abstract: Decentralized stochastic gradient descent (D-SGD) is an efficient method for large-scale distributed learning. Existing generalization studies mainly ad

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Urban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception

DGX agent

arXiv:2605.09936v1 Announce Type: new Abstract: We present Urban-ImageNet, a large-scale multi-modal dataset and evaluation benchmark for urban space perception from user-generated social media imager

model-releasesarxiv-cs-cv

12 May 2026

UserGPT Technical Report

arXiv:2605.08766v1 Announce Type: cross Abstract: Personalized user understanding from large-scale digital traces remains a fundamental challenge. Traditional user profiling methods rely on discrimina

UTS at PsyDefDetect: Multi-Agent Councils and Absence-Based Reasoning for Defense Mechanism Classification

arXiv:2605.09769v1 Announce Type: new Abstract: This paper describes our system for classifying psychological defense mechanisms in emotional support dialogues using the Defense Mechanism Rating Scale

V4FinBench: Benchmarking Tabular Foundation Models, LLMs, and Standard Methods on Corporate Bankruptcy Prediction

arXiv:2605.10896v1 Announce Type: new Abstract: Corporate bankruptcy prediction is a high-stakes financial task characterized by severe class imbalance and multi-horizon forecasting demands. Public da

Valid Best-Model Identification for LLM Evaluation via Low-Rank Factorization

arXiv:2605.10405v1 Announce Type: new Abstract: Selecting the best large language model (LLM) for a fixed benchmark is often expensive, since exhaustive evaluation requires running every model on ever

VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models

arXiv:2603.18113v2 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly shape content generation, interaction, and decision-making across the Web, aligning them with hum

VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.10485v1 Announce Type: new Abstract: Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominan

VeriContest: A Competitive-Programming Benchmark for Verifiable Code Generation

arXiv:2605.08553v1 Announce Type: cross Abstract: Large language models can generate useful code from natural language, but their outputs come without correctness guarantees. Verifiable code generatio

VFM-SDM: A vision foundation model-based framework for training-free, marker-free, and calibration-free structural displacement measurement

arXiv:2605.09677v1 Announce Type: new Abstract: Reliable displacement measurement is fundamental for structural health monitoring and digital engineering workflows, as it provides direct structural re

VidNum-1.4K: A Comprehensive Benchmark for Video-based Numerical Reasoning

arXiv:2604.03701v2 Announce Type: replace Abstract: Video-based numerical reasoning provides a premier arena for testing whether Vision-Language Models (VLMs) truly 'understand' real-world dynamics, a

VISOR: A Vision-Language Model-based Test Oracle for Testing Robot

model-releasesarxiv-cs-ro

arXiv:2605.10408v1 Announce Type: cross Abstract: Testing robots requires assessing whether they perform their intended tasks correctly, dependably, and with high quality, a challenge known as the tes

VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation

model-releasesarxiv-cs-ro

arXiv:2605.08886v1 Announce Type: cross Abstract: Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This

Visual-ERM: Reward Modeling for Visual Equivalence

arXiv:2603.13224v2 Announce Type: replace-cross Abstract: Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured r

VLADriver-RAG: Retrieval-Augmented Vision-Language-Action Models for Autonomous Driving

arXiv:2605.08133v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving, yet their reliance on implicit parametric

VORT: Adaptive Power-Law Memory for NLP Transformers

arXiv:2605.08966v1 Announce Type: new Abstract: Standard Transformers impose near-exponential decay on the influence of distant tokens, conflicting with the power-law structure of long-range dependenc

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning

arXiv:2605.08146v1 Announce Type: cross Abstract: Multi-model learning has attracted great attention in visual-text tasks. However, visual-tabular data, which plays a pivotal role in high-stakes domai

WATCH: Wide-Area Archaeological Site Tracking for Change Detection

arXiv:2605.08160v1 Announce Type: cross Abstract: Monitoring archaeological sites at scale is vital for protecting cultural heritage, yet pinpointing when disturbances occur remains difficult because

Weight Pruning Amplifies Bias: A Multi-Method Study of Compressed LLMs for Edge AI

arXiv:2605.08137v1 Announce Type: cross Abstract: Weight pruning is widely advocated for deploying Large Language Models on resource-constrained IoT and edge devices, yet its impact on model fairness

What Will Happen Next: Large Models-Driven Deduction for Emergency Instances

arXiv:2605.08599v1 Announce Type: new Abstract: Traditional simulation methods reproduce occurred emergency instances through presetting to assist people in risk assessment and emergency decision-maki

What's the plan? Metrics for implicit planning in LLMs and their application to rhyme generation and question answering

arXiv:2601.20164v2 Announce Type: replace-cross Abstract: Prior work suggests that language models, while trained on next token prediction, show implicit planning behavior: they may select the next to

When Adaptation Fails: A Gradient-Based Diagnosis of Collapsed Gating in Vision-Language Prompt Learning

arXiv:2605.09549v1 Announce Type: new Abstract: Adaptive prompting mechanisms have been proposed to enhance vision-language models by dynamically tailoring prompts to inputs. However, in frozen few-sh

When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning

arXiv:2605.09109v1 Announce Type: new Abstract: Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses s

When Attention Beats Fourier: Multi-Scale Transformers for PDE Solving on Irregular Domains

arXiv:2605.08318v1 Announce Type: cross Abstract: We study the problem of architecture selection for deep learning models trained to solve partial differential equations (PDEs), asking when transforme

When Does Non-Uniform Replay Matter in Reinforcement Learning?

arXiv:2605.10236v1 Announce Type: cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains unclear when and why non-uniform repla

When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications

arXiv:2605.10176v1 Announce Type: cross Abstract: Natural language interfaces to structured databases are becoming increasingly common, largely due to advances in large language models (LLMs) that ena

When Reviews Disagree: Fine-Grained Contradiction Analysis in Scientific Peer Reviews

arXiv:2605.10171v1 Announce Type: cross Abstract: Scientific peer reviews frequently contain conflicting expert judgments, and the increasing scale of conference submissions makes it challenging for A

When to Re-Commit: Temporal Abstraction Discovery for Long-Horizon Vision-Language Reasoning

arXiv:2605.09860v1 Announce Type: new Abstract: Long-horizon reasoning requires deciding not only what actions to take, but how deeply to commit before the next observation. We formalize this as commi

When to Trust Imagination: Adaptive Action Execution for World Action Models

arXiv:2605.06222v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) have recently emerged as a promising paradigm for robotic manipulation by jointly predicting future visual observat

Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing

arXiv:2605.10544v1 Announce Type: new Abstract: Long-context adaptation is often viewed as window scaling, but this misses a token-level supervision mismatch: in packed training with document masking,

Why Retrying Fails: Context Contamination in LLM Agent Pipelines

arXiv:2605.08563v1 Announce Type: new Abstract: When an LLM agent fails a multi-step tool-augmented task and retries, the failed attempt typically remains in its context window -- contaminating the ne

Why Zeroth-Order Adaptation May Forget Less: A Randomized Shaping Theory

arXiv:2605.10658v1 Announce Type: new Abstract: Continual learning requires new-task adaptation without damaging previously acquired capabilities. Recent forward-pass and zeroth-order (ZO) results sho

WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation

arXiv:2605.10912v1 Announce Type: new Abstract: Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However,

WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain

arXiv:2605.09511v1 Announce Type: new Abstract: Many downstream decisions in complex terrain require fast wind estimates at a small number of user-specified locations and heights for a given forecast

WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors

arXiv:2605.10434v1 Announce Type: new Abstract: Commercial video generation systems such as Seedance2.0 and Veo3.1 have rapidly improved, strengthening the view that video generators may be evolving i

You Have Been LaTeXpOsEd: A Systematic Analysis of Information Leakage in Preprint Archives Using Large Language Models

arXiv:2510.03761v2 Announce Type: replace-cross Abstract: The widespread use of preprint repositories such as arXiv has accelerated the communication of scientific results but also introduced overlook

Your Simulation Runs but Solves the Wrong Physics: PDE-Grounded Intent Verification for LLM-Generated Multiphysics Simulation Code

arXiv:2605.09360v1 Announce Type: cross Abstract: Execution-based evaluation of LLM-generated code implicitly treats successful execution as a proxy for correctness. In scientific simulation, this pro

Zero-Shot Chinese Character Recognition via Global-Local Dual-Branch Alignment and Hierarchical Inference

arXiv:2605.08814v1 Announce Type: new Abstract: Chinese character categories are extremely large, and unseen characters frequently arise in open-world scenarios, making zero-shot Chinese character rec

2.5-D Decomposition for LLM-Based Spatial Construction

arXiv:2605.07066v1 Announce Type: new Abstract: Autonomous systems that build structures from natural-language instructions need reliable spatial reasoning, yet large language models (LLMs) make syste

A Causal Diffusion Model for Video Reconstruction from Ultra-Low-Bitrate Representations

arXiv:2602.13837v2 Announce Type: replace Abstract: We study video reconstruction from ultra-low-bitrate representations, where the primary challenge shifts from encoding to decoding. In this regime,

A Hierarchical Ensemble Pipeline for Anomaly Detection in ESA Satellite Telemetry

arXiv:2605.06681v1 Announce Type: cross Abstract: A hierarchical ensemble pipeline is introduced to address anomaly detection in multivariate telemetry data provided by European Space Agency (ESA). Th

A Marine Debris Detection Framework for Ocean Robots via Self-Attention Enhancement and Feature Interaction Optimization

arXiv:2605.07388v1 Announce Type: new Abstract: Marine debris detection for ocean robot is crucial for ecological protection, yet performance is often degraded by low-quality images with blur, complex

A Reproducible Multi-Architecture Baseline for Token-Level Chinese Metaphor Identification under the MIPVU Framework

arXiv:2605.07170v1 Announce Type: new Abstract: Metaphor is pervasive in everyday language, yet token-level computational identification of metaphor-related words in Chinese under the MIPVU framework

A Reproducible Optimisation Protocol for Calibrating Prompt-Based Large Language Model Workflows in Evidence Synthesis

arXiv:2605.06937v1 Announce Type: new Abstract: This methods article presents a reproducible calibration workflow for prompt-based large language models (LLMs) in structured evidence-synthesis tasks.

A Unified and Controllable Framework for Layered Image Generation with Visual Effects

arXiv:2601.15507v2 Announce Type: replace Abstract: Recent image generation models produce impressive composites, but often fail to preserve the identity of user-provided content when editing specific

A^2RD: Agentic Autoregressive Diffusion for Long Video Consistency

arXiv:2605.06924v1 Announce Type: cross Abstract: Synthesizing consistent and coherent long video remains a fundamental challenge. Existing methods suffer from semantic drift and narrative collapse ov

Adapting Vision-Language Models for Neutrino Event Classification in High-Energy Physics

arXiv:2509.08461v3 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have demonstrated their remarkable capacity to process and reason over structured and unstruct

Adaptive Memory Decay for Log-Linear Attention

arXiv:2605.06946v1 Announce Type: cross Abstract: Sequence models face a fundamental tradeoff between memory capacity and computational efficiency. Transformers achieve expressive context modeling at