4 citations · 8 across the 6 of their papers we have counts for
6 papers
LLM4GEN: Leveraging Semantic Representation of LLMs for Text-to-Image Generation
Mushui Liu, Yuhang Ma, Yang Zhen +6
Diffusion models have exhibited substantial success in text-to-image generation. However, they often encounter challenges when dealing with complex and dense prompts involving mult…
XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques
Yu Xiong, Zhipeng Hu, Ye Huang +9
Reinforcement Learning (RL) has demonstrated substantial potential across diverse fields, yet understanding its decision-making process, especially in real-world scenarios where ra…
DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video
Zhimeng Zhang, Zhipeng Hu, Wenjin Deng +3
For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity du…
Zero-Shot Text-to-Parameter Translation for Game Character Auto-Creation
Rui Zhao, Wei Li, Zhipeng Hu +4
Recent popular Role-Playing Games (RPGs) saw the great success of character auto-creation systems. The bone-driven face model controlled by continuous parameters (like the position…
Tailoring Language Generation Models under Total Variation Distance
Haozhe Ji, Pei Ke, Zhipeng Hu +2
The standard paradigm of neural language generation adopts maximum likelihood estimation (MLE) as the optimizing method. From a distributional view, MLE in fact minimizes the Kullb…
Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework
Jian Guan, Zhenyu Yang, Rongsheng Zhang +2
Despite advances in generating fluent texts, existing pretraining models tend to attach incoherent event sequences to involved entities when generating narratives such as stories a…