Search: “framework”

arXiv:2503.10183v4 Announce Type: replace Abstract: Existing vision-language models (VLMs) often suffer from visual hallucination, where the generated responses contain inaccuracies that are not groun

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Safety

Tool-MCoT: Tool Augmented Multimodal Chain-of-Thought for Content Safety Moderation

DGX agent

arXiv:2604.06205v1 Announce Type: cross Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various media types. Wh

safetyarxiv-cs-ai

10 Apr 2026

Agents

TOOLCAD: Exploring Tool-Using Large Language Models in Text-to-CAD Generation with Reinforcement Learning

arXiv:2604.07960v1 Announce Type: cross Abstract: Computer-Aided Design (CAD) is an expert-level task that relies on long-horizon reasoning and coherent modeling actions. Large Language Models (LLMs)

agentsarxiv-cs-cl

Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval

model-releasesarxiv-cs-cv

arXiv:2512.08410v2 Announce Type: replace Abstract: Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose

Agents

Towards Resilient Intrusion Detection in CubeSats: Challenges, TinyML Solutions, and Future Directions

arXiv:2604.06411v1 Announce Type: cross Abstract: CubeSats have revolutionized access to space by providing affordable and accessible platforms for research and education. However, their reliance on C

agentsarxiv-cs-ai

Towards the Development of an LLM-Based Methodology for Automated Security Profiling in Compliance with Ukrainian Cybersecurity Regulations

arXiv:2604.06274v1 Announce Type: cross Abstract: In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to co

safetyarxiv-cs-ai

TSUBASA: Improving Long-Horizon Personalization via Evolving Memory and Self-Learning with Context Distillation

model-releasesarxiv-cs-cl

arXiv:2604.07894v1 Announce Type: new Abstract: Personalized large language models (PLLMs) have garnered significant attention for their ability to align outputs with individual's needs and preference

TwinLoop: Simulation-in-the-Loop Digital Twins for Online Multi-Agent Reinforcement Learning

arXiv:2604.06610v1 Announce Type: cross Abstract: Decentralised online learning enables runtime adaptation in cyber-physical multi-agent systems, but when operating conditions change, learned policies

safetyarxiv-cs-ai

Applications

UniLACT: Depth-Aware RGB Latent Action Learning for Vision-Language-Action Models

arXiv:2602.20231v2 Announce Type: replace-cross Abstract: Latent action representations learned from unlabeled videos have recently emerged as a promising paradigm for pretraining vision-language-acti

applicationsarxiv-cs-cv

Applications

Unsupervised Neural Network for Automated Classification of Surgical Urgency Levels in Medical Transcriptions

arXiv:2604.06214v1 Announce Type: cross Abstract: Efficient classification of surgical procedures by urgency is paramount to optimize patient care and resource allocation within healthcare systems. Th

applicationsarxiv-cs-ai

URMF: Uncertainty-aware Robust Multimodal Fusion for Multimodal Sarcasm Detection

arXiv:2604.06728v1 Announce Type: cross Abstract: Multimodal sarcasm detection (MSD) aims to identify sarcastic intent from semantic incongruity between text and image. Although recent methods have im

safetyarxiv-cs-ai

Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing

model-releasesarxiv-cs-cl

arXiv:2604.08401v1 Announce Type: cross Abstract: In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory. However

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

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 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

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

model-releasesarxiv-cs-cl

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

Research

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

researcharxiv-cs-cv

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