74 citations · 84 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 1 cited
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning
Jiasheng Ye, Zaixiang Zheng, Yu Bao +2
The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their po…
cs.CL2023★ 74 cited
Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey
Chen Ling, Xujiang Zhao, Jiaying Lu +21
Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of app…
cs.LG2023★ 9 cited
Structure-informed Language Models Are Protein Designers
Zaixiang Zheng, Yifan Deng, Dongyu Xue +3
This paper demonstrates that language models are strong structure-based protein designers. We present LM-Design, a generic approach to reprogramming sequence-based protein language…