2 citations · 2 across the 7 of their papers we have counts for
10 papers
PhysCaP: Grounding Code-as-Policy Agent with Physics-Informed Exploration
Chen-Yu Lin, Jing-Wen Chen, Hsueh-En Chang +8
We present PhysCaP, a Physics-Informed Code-as-Policy agent system for active perception in robotic manipulation. While vision-language-action policies excel at imitating demonstra…
Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu +4
Vision-Language-Action (VLA) tasks require reasoning over complex visual scenes and executing adaptive actions in dynamic environments. While recent studies on reasoning VLAs show…
TA-Prompting: Enhancing Video Large Language Models for Dense Video Captioning via Temporal Anchors
Wei-Yuan Cheng, Kai-Po Chang, Chi-Pin Huang +2
Dense video captioning aims to interpret and describe all temporally localized events throughout an input video. Recent state-of-the-art methods leverage large language models (LLM…
Mitigating Object and Action Hallucinations in Multimodal LLMs via Self-Augmented Contrastive Alignment
Kai-Po Chang, Wei-Yuan Cheng, Chi-Pin Huang +2
Recent advancement in multimodal LLMs (MLLMs) has demonstrated their remarkable capability to generate descriptive captions for input videos. However, these models suffer from fact…
Continual Personalization for Diffusion Models
Yu-Chien Liao, Jr-Jen Chen, Chi-Pin Huang +3
Updating diffusion models in an incremental setting would be practical in real-world applications yet computationally challenging. We present a novel learning strategy of Concept N…
ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Chi-Pin Huang, Yueh-Hua Wu, Min-Hung Chen +2
Vision-language-action (VLA) reasoning tasks require agents to interpret multimodal instructions, perform long-horizon planning, and act adaptively in dynamic environments. Existin…
VideoMage: Multi-Subject and Motion Customization of Text-to-Video Diffusion Models
Chi-Pin Huang, Yen-Siang Wu, Hung-Kai Chung +3
Customized text-to-video generation aims to produce high-quality videos that incorporate user-specified subject identities or motion patterns. However, existing methods mainly focu…
MotionMatcher: Motion Customization of Text-to-Video Diffusion Models via Motion Feature Matching
Yen-Siang Wu, Chi-Pin Huang, Fu-En Yang +1
Text-to-video (T2V) diffusion models have shown promising capabilities in synthesizing realistic videos from input text prompts. However, the input text description alone provides…
Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models
Yu-Chu Yu, Chi-Pin Huang, Jr-Jen Chen +4
Large-scale vision-language models (VLMs) have shown a strong zero-shot generalization capability on unseen-domain data. However, adapting pre-trained VLMs to a sequence of downstr…
Receler: Reliable Concept Erasing of Text-to-Image Diffusion Models via Lightweight Erasers
Chi-Pin Huang, Kai-Po Chang, Chung-Ting Tsai +3
Concept erasure in text-to-image diffusion models aims to disable pre-trained diffusion models from generating images related to a target concept. To perform reliable concept erasu…