activity
20222026
most citedEmpowering Diffusion Models on the Embedding Space for Text Generation

12 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.IR2026

DREAM Technical Report

Bin Zhang, Bowen Zheng, Chao Yi +74

Industrial recommender systems commonly use cascaded retrieval, ranking, and re-ranking pipelines. Although efficient, these pipelines fragment information and objectives across mo…

cs.IR2026

RecGPT-V3 Technical Report

Bowen Zheng, Chao Yi, Dian Chen +26

Large language models (LLMs) are transforming recommender systems from matching co-occurrence patterns in historical behavior toward reasoning about the intent that drives it. RecG…

cs.IR2025

RecGPT-V2 Technical Report

Chao Yi, Dian Chen, Gaoyang Guo +32

Large language models (LLMs) have demonstrated remarkable potential in transforming recommender systems from implicit behavioral pattern matching to explicit intent reasoning. Whil…

cs.IR2025

Interactive Recommendation Agent with Active User Commands

Jiakai Tang, Yujie Luo, Xunke Xi +12

Traditional recommender systems rely on passive feedback mechanisms that limit users to simple choices such as like and dislike. However, these coarse-grained signals fail to captu…

cs.IR2025

RecGPT Technical Report

Chao Yi, Dian Chen, Gaoyang Guo +51

Recommender systems are among the most impactful applications of artificial intelligence, serving as critical infrastructure connecting users, merchants, and platforms. However, mo…

cs.CL2025

Unifying Continuous and Discrete Text Diffusion with Non-simultaneous Diffusion Processes

Bocheng Li, Zhujin Gao, Linli Xu

Diffusion models have emerged as a promising approach for text generation, with recent works falling into two main categories: discrete and continuous diffusion models. Discrete di…

cs.CL2023

DiffS2UT: A Semantic Preserving Diffusion Model for Textless Direct Speech-to-Speech Translation

Yongxin Zhu, Zhujin Gao, Xinyuan Zhou +2

While Diffusion Generative Models have achieved great success on image generation tasks, how to efficiently and effectively incorporate them into speech generation especially trans…

cs.CL2022★ 12 cited

Empowering Diffusion Models on the Embedding Space for Text Generation

Zhujin Gao, Junliang Guo, Xu Tan +4

Diffusion models have achieved state-of-the-art synthesis quality on both visual and audio tasks, and recent works further adapt them to textual data by diffusing on the embedding…