12 citations · 20 across the 4 of their papers we have counts for
6 papers
Distilling Counterfactual Reasoning from Language to Vision: Causal Graph Guided Post-Training for Video Understanding
Yuefei Chen, Jiang Liu, Xiaodong Lin +1
Vision Language Models (VLMs) have recently shown significant advancements in video understanding, especially in feature alignment, event reasoning, and instruction-following tasks…
Interactive Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning
He Zhang, Ying Sun, Weiyu Guo +4
Personalized interior decoration design often incurs high labor costs. Recent efforts in developing intelligent interior design systems have focused on generating textual requireme…
Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models
Fobo Shi, Peijun Qing, Dong Yang +5
Prompt engineering is an essential technique for enhancing the abilities of large language models (LLMs) by providing explicit and specific instructions. It enables LLMs to excel i…
Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback
Yiqi Lin, Hao Wu, Ruichen Wang +4
Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within…
Compositional Text-to-Image Synthesis with Attention Map Control of Diffusion Models
Ruichen Wang, Zekang Chen, Chen Chen +3
Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align…
Edit Everything: A Text-Guided Generative System for Images Editing
Defeng Xie, Ruichen Wang, Jian Ma +5
We introduce a new generative system called Edit Everything, which can take image and text inputs and produce image outputs. Edit Everything allows users to edit images using simpl…