8 papers · 1 filter
TacClaw-Infinity: A Large-Scale Vision-Tactile-Language-Action Dataset for Dexterous Manipulation
Fucai Zhu, Xidong Zhang, Yichi Zhang +23
Large-scale robot learning increasingly relies on diverse human demonstrations, yet tactile manipulation data remain difficult to scale, and existing multimodal datasets often lack…
SaTPO: Text-to-Image Safety Alignment via Transition Preference Optimization
Ziyi Fang, Jingzhi Li, Xiaojun Jia +3
Safety alignment of text-to-image diffusion models aims to suppress harmful content without compromising useful generation capabilities. However, preferences over completed images…
ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models
Ruochen Zhang, Yao Huang, Yitong Sun +5
While Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, their reliability is threatened by multimodal implicit risks. Unlike explicit t…
AdvTiles: Physical Adversarial Camouflage Clothing against Person Detectors via Learnable Tiles
Jinlei Wang, Jiahuan Long, Mingkai Sun +9
Physical adversarial attacks against person detectors have evolved from localized patches to full-body textures. However, achieving both visual naturalness and strong attack effect…
UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation
Yao Huang, Yitong Sun, Huanran Chen +8
Despite the impressive generative capabilities of text-to-image diffusion models, they remain vulnerable to implicit sexual prompts, where subtle cues disguised as benign terms or…
AlloSpatial: Agentic Harness Framework for Spatial Reasoning in Foundation Models
Shouwei Ruan, Bin Wang, Zhenyu Wu +5
Multimodal Foundation Models (MFMs) have made substantial progress, yet remain fragile in spatial reasoning over the physical world. A key bottleneck lies in their inability to tra…
MESA: Improving MoE Safety Alignment via Decentralized Expertise
Yitong Sun, Yao Huang, Teng Li +5
Mixture-of-Experts (MoE) architectures scale Large Language Models (LLMs) efficiently, enabling greater capacity with reduced computational cost by dynamically routing inputs to re…
Mind over Space: Can Multimodal Large Language Models Mentally Navigate?
Qihui Zhu, Shouwei Ruan, Xiao Yang +6
Despite the widespread adoption of MLLMs in embodied agents, their capabilities remain largely confined to reactive planning from immediate observations, consistently failing in sp…