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UsefulBench: Towards Decision-Useful Information as a Target for Information Retrieval

arXiv:2604.15827v1 Announce Type: cross Abstract: Conventional information retrieval is concerned with identifying the relevance of texts for a given query. Yet, the conventional definition of relevan

safetyarxiv-cs-cl

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Using Large Language Models and Knowledge Graphs to Improve the Interpretability of Machine Learning Models in Manufacturing

DGX agent

arXiv:2604.16280v1 Announce Type: new Abstract: Explaining Machine Learning (ML) results in a transparent and user-friendly manner remains a challenging task of Explainable Artificial Intelligence (XA

applicationsarxiv-cs-ai

20 Apr 2026

VADF: Vision-Adaptive Diffusion Policy Framework for Efficient Robotic Manipulation

arXiv:2604.15938v1 Announce Type: new Abstract: Diffusion policies are becoming mainstream in robotic manipulation but suffer from hard negative class imbalance due to uniform sampling and lack of sam

safetyarxiv-cs-ro

VEFX-Bench: A Holistic Benchmark for Generic Video Editing and Visual Effects

arXiv:2604.16272v1 Announce Type: cross Abstract: As AI-assisted video creation becomes increasingly practical, instruction-guided video editing has become essential for refining generated or captured

VeriCWEty: Embedding enabled Line-Level CWE Detection in Verilog

arXiv:2604.15375v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown significant improvement in RTL code generation. Despite the advances, the generated code is often riddled with

Verification Modulo Tested Library Contracts

arXiv:2604.15533v1 Announce Type: cross Abstract: We consider the problem of verification modulo tested library contracts as a step towards automating the verification of client programs that use comp

researcharxiv-cs-lg

VeriGraph: Scene Graphs for Execution Verifiable Robot Planning

arXiv:2411.10446v3 Announce Type: replace-cross Abstract: Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrec

VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation

arXiv:2510.27617v2 Announce Type: replace Abstract: Automation of Register Transfer Level (RTL) design can help developers meet increasing computational demands. Large Language Models (LLMs) show prom

Local Ai

VeRVE: Versatile Retrieval for Videos via Unified Embeddings

arXiv:2601.12193v3 Announce Type: replace Abstract: Modern video retrieval systems are expected to handle diverse tasks ranging from corpus-level retrieval, fine-grained moment localization to flexibl

local-aiarxiv-cs-cv

VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck

arXiv:2601.05547v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in multimodal tasks, but remain susceptible to hallucinations, where gener

Video-STAR: Reinforcing Open-Vocabulary Action Recognition with Tools

arXiv:2510.08480v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have demonstrated remarkable potential in bridging visual and textual reasoning, yet their reliance on text

vla-eval: A Unified Evaluation Harness for Vision-Language-Action Models

arXiv:2603.13966v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pip

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models

arXiv:2512.14554v5 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) has enabled new possibilities for applying artificial intelligence within the legal doma

Local Ai

VoodooNet: Achieving Analytic Ground States via High-Dimensional Random Projections

arXiv:2604.15613v1 Announce Type: cross Abstract: We present VoodooNet, a non-iterative neural architecture that replaces the stochastic gradient descent (SGD) paradigm with a closed-form analytic sol

local-aiarxiv-cs-ai

WARBERT: A Hierarchical BERT-based Model for Web API Recommendation

arXiv:2509.23175v2 Announce Type: replace-cross Abstract: With the rise of Web 2.0 and microservices, the increasing availability of Web APIs has intensified the need for effective recommendation syst

Watching Movies Like a Human: Egocentric Emotion Understanding for Embodied Companions

model-releasesarxiv-cs-cv

arXiv:2604.15823v1 Announce Type: new Abstract: Embodied robotic agents often perceive movies through an egocentric screen-view interface rather than native cinematic footage, introducing domain shift

Weak-Link Optimization for Multi-Agent Reasoning and Collaboration

arXiv:2604.15972v1 Announce Type: new Abstract: LLM-driven multi-agent frameworks address complex reasoning tasks through multi-role collaboration. However, existing approaches often suffer from reaso

Weak-to-Strong Knowledge Distillation Accelerates Visual Learning

arXiv:2604.15451v1 Announce Type: new Abstract: Large-scale visual learning is increasingly limited by training cost. Existing knowledge distillation methods transfer from a stronger teacher to a weak

(Weighted) Adaptive Radius Near Neighbor Search: Evaluation for WiFi Fingerprint-based Positioning

arXiv:2604.15940v1 Announce Type: new Abstract: Fixed Radius Near Neighbor (FRNN) search is an alternative to the widely used k Nearest Neighbors (kNN) search. Unlike kNN, FRNN determines a label or a

researcharxiv-cs-lg

What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context

arXiv:2506.02261v3 Announce Type: replace-cross Abstract: What enables large language models (LLMs) to effectively model user preferences in sequential recommendation? Our investigation reveals that e

When Cultures Meet: Multicultural Text-to-Image Generation

arXiv:2502.15972v2 Announce Type: replace-cross Abstract: Text-to-image generation models have achieved strong performance in culturally homogeneous settings, yet their ability to generate multicultur

When Do Early-Exit Networks Generalize? A PAC-Bayesian Theory of Adaptive Depth

arXiv:2604.15764v1 Announce Type: cross Abstract: Early-exit neural networks enable adaptive computation by allowing confident predictions to exit at intermediate layers, achieving 2-8imes inference s

When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models

arXiv:2510.09689v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been augmented with web search to overcome the limitations of the static knowledge boundary by accessing up-

safetyarxiv-cs-ai

When Surfaces Lie: Exploiting Wrinkle-Induced Attention Shift to Attack Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2603.27759v3 Announce Type: replace Abstract: Visual-Language Models (VLMs) have demonstrated exceptional cross-modal understanding across various tasks, including zero-shot classification, imag

Applications

When the Loop Closes: Architectural Limits of In-Context Isolation, Metacognitive Co-option, and the Two-Target Design Problem in Human-LLM Systems

arXiv:2604.15343v1 Announce Type: cross Abstract: We report a detailed autoethnographic case study of a single-subject who deliberately constructed and operated a multi-modal prompt-engineering system

applicationsarxiv-cs-ai

Local Ai

Where Do Vision-Language Models Fail? World Scale Analysis for Image Geolocalization

arXiv:2604.16248v1 Announce Type: new Abstract: Image geolocalization has traditionally been addressed through retrieval-based place recognition or geometry-based visual localization pipelines. Recent

local-aiarxiv-cs-cv

Where does output diversity collapse in post-training?

arXiv:2604.16027v1 Announce Type: cross Abstract: Post-trained language models produce less varied outputs than their base counterparts. This output diversity collapse undermines inference-time scalin

Whose Facts Win? LLM Source Preferences under Knowledge Conflicts

arXiv:2601.03746v3 Announce Type: replace Abstract: As large language models (LLMs) are more frequently used in retrieval-augmented generation pipelines, it is increasingly relevant to study their beh

safetyarxiv-cs-cl

Why Colors Make Clustering Harder:Global Integrality Gaps, the Price of Fairness, and Color-Coupled Algorithms in Chromatic Correlation Clustering

arXiv:2604.15738v1 Announce Type: new Abstract: Chromatic Correlation Clustering (CCC) extends Correlation Clustering by assigning semantic colors to edges and requiring each cluster to receive a sing

Why Fine-Tuning Encourages Hallucinations and How to Fix It

arXiv:2604.15574v1 Announce Type: cross Abstract: Large language models are prone to hallucinating factually incorrect statements. A key source of these errors is exposure to new factual information t

WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback

arXiv:2408.15549v4 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, aligning these models with human preferences has emerged as a critical challenge. Traditional a

safetyarxiv-cs-cl

Winner of CVPR2026 NTIRE Challenge on Image Shadow Removal: Semantic and Geometric Guidance for Shadow Removal via Cascaded Refinement

arXiv:2604.16177v1 Announce Type: new Abstract: We present a three-stage progressive shadow-removal pipeline for the CVPR2026 NTIRE WSRD+ challenge. Built on OmniSR, our method treats deshadowing as i

Wisdom is Knowing What not to Say: Hallucination-Free LLMs Unlearning via Attention Shifting

model-releasesarxiv-cs-cl

arXiv:2510.17210v3 Announce Type: replace Abstract: The increase in computing power and the necessity of AI-assisted decision-making boost the growing application of large language models (LLMs). Alon

WiseMind: a knowledge-guided multi-agent framework for accurate and empathetic psychiatric diagnosis

arXiv:2502.20689v4 Announce Type: replace Abstract: Large Language Models (LLMs) offer promising opportunities to support mental healthcare workflows, yet they often lack the structured clinical reaso

Zero-Shot Scalable Resilience in UAV Swarms: A Decentralized Imitation Learning Framework with Physics-Informed Graph Interactions

arXiv:2604.15762v1 Announce Type: new Abstract: Large-scale Unmanned Aerial Vehicle (UAV) failures can split an unmanned aerial vehicle swarm network into disconnected sub-networks, making decentraliz

Zoom Consistency: A Free Confidence Signal in Multi-Step Visual Grounding Pipelines

arXiv:2604.15376v1 Announce Type: cross Abstract: Multi-step zoom-in pipelines are widely used for GUI grounding, yet the intermediate predictions they produce are typically discarded after coordinate

3AM: 3egment Anything with Geometric Consistency in Videos

arXiv:2601.08831v5 Announce Type: replace Abstract: Video object segmentation methods like SAM2 achieve strong performance through memory-based architectures but struggle under large viewpoint changes

3D Conditional Image Synthesis of Left Atrial LGE MRI from Composite Semantic Masks

arXiv:2601.04588v2 Announce Type: replace Abstract: Segmentation of the left atrial (LA) wall and endocardium from late gadolinium-enhanced (LGE) MRI is essential for quantifying atrial fibrosis in pa

3D Instruction Ambiguity Detection

arXiv:2601.05991v2 Announce Type: replace Abstract: In safety-critical domains, linguistic ambiguity can have severe consequences; a vague command like 'Pass me the vial' in a surgical setting could l

4D Radar Gaussian Modeling and Scan Matching with RCS

arXiv:2604.14868v1 Announce Type: new Abstract: 4D millimeter-wave (mmWave) radars are increasingly used in robotics, as they offer robustness against adverse environmental conditions. Besides the usu

A deep learning framework for glomeruli segmentation with boundary attention

arXiv:2604.14263v1 Announce Type: cross Abstract: Accurate detection and segmentation of glomeruli in kidney tissue are essential for diagnostic applications. Traditional deep learning methods primari

A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics

arXiv:2604.15215v1 Announce Type: new Abstract: We present a novel hierarchical spatiotemporal action tokenizer for in-context imitation learning. We first propose a hierarchical approach, which consi

A Linguistics-Aware LLM Watermarking via Syntactic Predictability

arXiv:2510.13829v3 Announce Type: replace Abstract: As large language models (LLMs) continue to advance rapidly, reliable governance tools have become critical. Publicly verifiable watermarking is par

researcharxiv-cs-cl

A Mechanistic Account of Attention Sinks in GPT-2: One Circuit, Broader Implications for Mitigation

arXiv:2604.14722v1 Announce Type: new Abstract: Transformers commonly exhibit an attention sink: disproportionately high attention to the first position. We study this behavior in GPT-2-style models w

A multi-platform LiDAR dataset for standardized forest inventory measurement at long term ecological monitoring sites

model-releasesarxiv-cs-ro

arXiv:2604.14635v1 Announce Type: new Abstract: We present a curated multi-platform LiDAR reference dataset from an instrumented ICOS forest plot, explicitly designed to support calibration, benchmark

A Multimodal Data Collection Framework for Dialogue-Driven Assistive Robotics to Clarify Ambiguities: A Wizard-of-Oz Pilot Study

arXiv:2601.16870v2 Announce Type: replace Abstract: Integrated control of wheelchairs and wheelchair-mounted robotic arms (WMRAs) has strong potential to increase independence for users with severe mo

A Nonasymptotic Theory of Gain-Dependent Error Dynamics in Behavior Cloning

arXiv:2604.14484v1 Announce Type: new Abstract: Behavior cloning (BC) policies on position-controlled robots inherit the closed-loop response of the underlying PD controller, yet the effect of control

A Nonlinear Separation Principle: Applications to Neural Networks, Control and Learning

model-releasesarxiv-cs-lg

arXiv:2604.15238v1 Announce Type: cross Abstract: This paper investigates continuous-time and discrete-time firing-rate and Hopfield recurrent neural networks (RNNs), with applications in nonlinear co