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VLMShield: Efficient and Robust Defense of Vision-Language Models against Malicious Prompts

arXiv:2604.06502v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face significant safety vulnerabilities from malicious prompt attacks due to weakened alignment during visual integration.

safetyarxiv-cs-lg

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VSAS-BENCH: Real-Time Evaluation of Visual Streaming Assistant Models

DGX agent

arXiv:2604.07634v1 Announce Type: new Abstract: Streaming vision-language models (VLMs) continuously generate responses given an instruction prompt and an online stream of input frames. This is a core

model-releasesarxiv-cs-cv

10 Apr 2026

WASD: Locating Critical Neurons as Sufficient Conditions for Explaining and Controlling LLM Behavior

arXiv:2603.18474v2 Announce Type: replace Abstract: Precise behavioral control of large language models (LLMs) is critical for complex applications. However, existing methods often incur high training

Weakly Supervised Distillation of Hallucination Signals into Transformer Representations

model-releasesarxiv-cs-ai

arXiv:2604.06277v1 Announce Type: new Abstract: Existing hallucination detection methods for large language models (LLMs) rely on external verification at inference time, requiring gold answers, retri

Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow

arXiv:2604.08313v1 Announce Type: new Abstract: Dense annotations, such as segmentation masks, are expensive and time-consuming to obtain, especially for 3D medical images where expert voxel-wise labe

Weaves, Wires, and Morphisms: Formalizing and Implementing the Algebra of Deep Learning

arXiv:2604.07242v1 Announce Type: new Abstract: Despite deep learning models running well-defined mathematical functions, we lack a formal mathematical framework for describing model architectures. Ad

researcharxiv-cs-lg

WebExpert: domain-aware web agents with critic-guided expert experience for high-precision search

arXiv:2604.06177v1 Announce Type: cross Abstract: Specialized web tasks in finance, biomedicine, and pharmaceuticals remain challenging due to missing domain priors: queries drift, evidence is noisy,

safetyarxiv-cs-ai

WebSP-Eval: Evaluating Web Agents on Website Security and Privacy Tasks

arXiv:2604.06367v1 Announce Type: cross Abstract: Web agents automate browser tasks, ranging from simple form completion to complex workflows like ordering groceries. While current benchmarks evaluate

safetyarxiv-cs-ai

Weight Group-wise Post-Training Quantization for Medical Foundation Model

arXiv:2604.07674v1 Announce Type: new Abstract: Foundation models have achieved remarkable results in medical image analysis. However, its large network architecture and high computational complexity

Weighted Bayesian Conformal Prediction

model-releasesarxiv-cs-lg

arXiv:2604.06464v1 Announce Type: new Abstract: Conformal prediction provides distribution-free prediction intervals with finite-sample coverage guarantees, and recent work by Snell & Griffiths refra

Tutorials

What do Language Models Learn and When? The Implicit Curriculum Hypothesis

arXiv:2604.08510v1 Announce Type: new Abstract: Large language models (LLMs) can perform remarkably complex tasks, yet the fine-grained details of how these capabilities emerge during pretraining rema

tutorialsarxiv-cs-cl

What Drives Representation Steering? A Mechanistic Case Study on Steering Refusal

arXiv:2604.08524v1 Announce Type: cross Abstract: Applying steering vectors to large language models (LLMs) is an efficient and effective model alignment technique, but we lack an interpretable explan

safetyarxiv-cs-cl

What Makes an Ideal Quote? Recommending 'Unexpected yet Rational' Quotations via Novelty

arXiv:2602.22220v2 Announce Type: replace-cross Abstract: Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize sur

safetyarxiv-cs-ai

What They Saw, Not Just Where They Looked: Semantic Scanpath Similarity via VLMs and NLP metric

arXiv:2604.08494v1 Announce Type: cross Abstract: Scanpath similarity metrics are central to eye-movement research, yet existing methods predominantly evaluate spatial and temporal alignment while neg

safetyarxiv-cs-cl

What's Missing in Screen-to-Action? Towards a UI-in-the-Loop Paradigm for Multimodal GUI Reasoning

model-releasesarxiv-cs-ai

arXiv:2604.06995v1 Announce Type: new Abstract: Existing Graphical User Interface (GUI) reasoning tasks remain challenging, particularly in UI understanding. Current methods typically rely on direct s

When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction

arXiv:2604.06558v1 Announce Type: new Abstract: We present the first systematic study of when target context helps molecular property prediction, evaluating context conditioning across 10 diverse prot

researcharxiv-cs-lg

When Fine-Tuning Changes the Evidence: Architecture-Dependent Semantic Drift in Chest X-Ray Explanations

arXiv:2604.08513v1 Announce Type: new Abstract: Transfer learning followed by fine-tuning is widely adopted in medical image classification due to consistent gains in diagnostic performance. However,

When Numbers Speak: Aligning Textual Numerals and Visual Instances in Text-to-Video Diffusion Models

arXiv:2604.08546v1 Announce Type: new Abstract: Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a

safetyarxiv-cs-cv

When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection

arXiv:2510.12476v2 Announce Type: replace Abstract: Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this abi

When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't

model-releasesarxiv-cs-ai

arXiv:2604.06422v1 Announce Type: cross Abstract: Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adher

When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning

arXiv:2604.08281v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of

Which Way Does Time Flow? A Psychophysics-Grounded Evaluation for Vision-Language Models

arXiv:2510.26241v5 Announce Type: replace-cross Abstract: Modern vision-language models (VLMs) excel at many multimodal tasks, yet their grasp of temporal information in video remains weak and has not

Why Are We Lonely? Leveraging LLMs to Measure and Understand Loneliness in Caregivers and Non-caregivers

arXiv:2604.07834v1 Announce Type: new Abstract: This paper presents an LLM-driven approach for constructing diverse social media datasets to measure and compare loneliness in the caregiver and non-car

Agents

'Why This Avoidance Maneuver?' Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation

arXiv:2604.08032v1 Announce Type: cross Abstract: Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system p

agentsarxiv-cs-ro

Agents

Working Paper: Towards a Category-theoretic Comparative Framework for Artificial General Intelligence

arXiv:2603.28906v2 Announce Type: replace Abstract: AGI has become the Holly Grail of AI with the promise of level intelligence and the major Tech companies around the world are investing unprecedente

agentsarxiv-cs-ai

WorldMAP: Bootstrapping Vision-Language Navigation Trajectory Prediction with Generative World Models

arXiv:2604.07957v1 Announce Type: cross Abstract: Vision-language models (VLMs) and generative world models are opening new opportunities for embodied navigation. VLMs are increasingly used as direct

WRAP++: Web discoveRy Amplified Pretraining

arXiv:2604.06829v2 Announce Type: cross Abstract: Synthetic data rephrasing has emerged as a powerful technique for enhancing knowledge acquisition during large language model (LLM) pretraining. Howev

researcharxiv-cs-ai

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects

arXiv:2604.07759v1 Announce Type: new Abstract: Ship detection for navigation is a fundamental perception task in intelligent waterway transportation systems. However, existing public ship detection d

XR-CareerAssist: An Immersive Platform for Personalised Career Guidance Leveraging Extended Reality and Multimodal AI

arXiv:2604.06901v1 Announce Type: cross Abstract: Conventional career guidance platforms rely on static, text-driven interfaces that struggle to engage users or deliver personalised, evidence-based in

researcharxiv-cs-ai

You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging

model-releasesarxiv-cs-cv

arXiv:2503.06717v3 Announce Type: replace Abstract: Interactive segmentation uses real-time user inputs, such as mouse clicks, to iteratively refine model predictions. Although not originally designed

Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials

arXiv:2602.22251v3 Announce Type: replace-cross Abstract: General-purpose 3D chemical modeling encompasses molecules and materials, requiring both generative and predictive capabilities. However, most

researcharxiv-cs-ai

Hardware

ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training

arXiv:2603.04385v3 Announce Type: replace Abstract: Feed-forward transformer models have driven rapid progress in 3D vision, but state-of-the-art methods such as VGGT and pi^3 have a computational

hardwarearxiv-cs-cv