1 citations · 1 across the 9 of their papers we have counts for
9 papers
VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL
Fengyuan Dai, Zifeng Zhuang, Yufei Huang +4
Diffusion models have emerged as powerful generative tools across various domains, yet tailoring pre-trained models to exhibit specific desirable properties remains challenging. Wh…
Exploring the Evolution of Physics Cognition in Video Generation: A Survey
Minghui Lin, Xiang Wang, Yishan Wang +8
Recent advancements in video generation have witnessed significant progress, especially with the rapid advancement of diffusion models. Despite this, their deficiencies in physical…
Humanoid-VLA: Towards Universal Humanoid Control with Visual Integration
Pengxiang Ding, Jianfei Ma, Xinyang Tong +13
This paper addresses the limitations of current humanoid robot control frameworks, which primarily rely on reactive mechanisms and lack autonomous interaction capabilities due to d…
Filter, Correlate, Compress: Training-Free Token Reduction for MLLM Acceleration
Yuhang Han, Xuyang Liu, Zihan Zhang +6
The quadratic complexity of Multimodal Large Language Models (MLLMs) with respect to context length poses significant computational and memory challenges, hindering their real-worl…
Focus-Consistent Multi-Level Aggregation for Compositional Zero-Shot Learning
Fengyuan Dai, Siteng Huang, Min Zhang +2
To transfer knowledge from seen attribute-object compositions to recognize unseen ones, recent compositional zero-shot learning (CZSL) methods mainly discuss the optimal classifica…
M2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension
Xuyang Liu, Ting Liu, Siteng Huang +6
Referring expression comprehension (REC) is a vision-language task to locate a target object in an image based on a language expression. Fully fine-tuning general-purpose pre-train…
DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding
Ting Liu, Xuyang Liu, Siteng Huang +5
Visual grounding (VG) is a challenging task to localize an object in an image based on a textual description. Recent surge in the scale of VG models has substantially improved perf…
Learning Disentangled Identifiers for Action-Customized Text-to-Image Generation
Siteng Huang, Biao Gong, Yutong Feng +4
This study focuses on a novel task in text-to-image (T2I) generation, namely action customization. The objective of this task is to learn the co-existing action from limited data a…
VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders
Xuyang Liu, Siteng Huang, Yachen Kang +2
Large-scale text-to-image diffusion models have shown impressive capabilities for generative tasks by leveraging strong vision-language alignment from pre-training. However, most v…