activity
20212025
most citedInteractive Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning

12 citations · 35 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2025

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…

cs.MM2023★ 12 cited

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…

cs.CL2023★ 5 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 2 cited

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…

cs.CV2023★ 7 cited

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…

cs.CV2023★ 3 cited

GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation

Jian Ma, Mingjun Zhao, Chen Chen +4

Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user i…

cs.CV2023★ 5 cited

CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout

Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang +4

Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusi…

cs.AI2021

Learning to Walk with Dual Agents for Knowledge Graph Reasoning

Denghui Zhang, Zixuan Yuan, Hao Liu +2

Graph walking based on reinforcement learning (RL) has shown great success in navigating an agent to automatically complete various reasoning tasks over an incomplete knowledge gra…