1 citations · 1 across the 4 of their papers we have counts for
4 papers
Automating Exploratory Proteomics Research via Language Models
Ning Ding, Shang Qu, Linhai Xie +13
With the development of artificial intelligence, its contribution to science is evolving from simulating a complex problem to automating entire research processes and producing nov…
Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention
Xingtai Lv, Ning Ding, Kaiyan Zhang +3
Improving the effectiveness and efficiency of large language models (LLMs) simultaneously is a critical yet challenging research goal. In this paper, we find that low-rank pre-trai…
Mastering Text, Code and Math Simultaneously via Fusing Highly Specialized Language Models
Ning Ding, Yulin Chen, Ganqu Cui +6
Underlying data distributions of natural language, programming code, and mathematical symbols vary vastly, presenting a complex challenge for large language models (LLMs) that stri…
Sparse Low-rank Adaptation of Pre-trained Language Models
Ning Ding, Xingtai Lv, Qiaosen Wang +4
Fine-tuning pre-trained large language models in a parameter-efficient manner is widely studied for its effectiveness and efficiency. The popular method of low-rank adaptation (LoR…