activity
20212024
most citedFuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization

36 citations · 75 across the 7 of their papers we have counts for

collaborators

6 papers

cs.CL2024

Language Rectified Flow: Advancing Diffusion Language Generation with Probabilistic Flows

Shujian Zhang, Lemeng Wu, Chengyue Gong +1

Recent works have demonstrated success in controlling sentence attributes (, sentiment) and structure (, syntactic structure) based on the diffusion language model. A k…

cs.CL202326 cited

AutoML-GPT: Automatic Machine Learning with GPT

Shujian Zhang, Chengyue Gong, Lemeng Wu +2

AI tasks encompass a wide range of domains and fields. While numerous AI models have been designed for specific tasks and applications, they often require considerable human effort…

cs.LG20237 cited

POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models

Korawat Tanwisuth, Shujian Zhang, Huangjie Zheng +2

Through prompting, large-scale pre-trained models have become more expressive and powerful, gaining significant attention in recent years. Though these big models have zero-shot ca…

cs.CL20236 cited

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

Yihao Feng, Shentao Yang, Shujian Zhang +4

When learning task-oriented dialogue (ToD) agents, reinforcement learning (RL) techniques can naturally be utilized to train dialogue strategies to achieve user-specific goals. Pri…

cs.LG2023

A Prototype-Oriented Clustering for Domain Shift with Source Privacy

Korawat Tanwisuth, Shujian Zhang, Pengcheng He +1

Unsupervised clustering under domain shift (UCDS) studies how to transfer the knowledge from abundant unlabeled data from multiple source domains to learn the representation of the…

cs.CV202136 cited

FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization

Xingchao Liu, Chengyue Gong, Lemeng Wu +3

Generating images from natural language instructions is an intriguing yet highly challenging task. We approach text-to-image generation by combining the power of the retrained CLIP…