9 citations · 9 across the 1 of their papers we have counts for
3 papers
cs.CL2023
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
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…