3 papers
cs.CV2026
PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration
Han Wang, Zijun Wang, Shuoshuo Xue +6
Action-conditioned world models are a key component of embodied AI, serving as scalable policy evaluators that reduce reliance on expensive real-world rollouts. To accurately captu…
cs.CV2026
Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models
Yuriel Ryan, Hei Man Ip, Adriel Kuek +2
Current vision language models face hallucination and robustness issues against ambiguous or corrupted modalities. We hypothesize that these issues can be addressed by exploiting t…
cs.LG2026
DreamReader: An Interpretability Toolkit for Text-to-Image Models
Nirmalendu Prakash, Narmeen Oozeer, Michael Lan +6
Despite the rapid adoption of text-to-image (T2I) diffusion models, causal and representation-level analysis remains fragmented and largely limited to isolated probing techniques.…