9 citations · 13 across the 5 of their papers we have counts for
6 papers
Aligning Protein Conformation Ensemble Generation with Physical Feedback
Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu +4
Protein dynamics play a crucial role in protein biological functions and properties, and their traditional study typically relies on time-consuming molecular dynamics (MD) simulati…
Multi-Scale Representation Learning for Protein Fitness Prediction
Zuobai Zhang, Pascal Notin, Yining Huang +5
Designing novel functional proteins crucially depends on accurately modeling their fitness landscape. Given the limited availability of functional annotations from wet-lab experime…
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques
Megh Thakkar, Quentin Fournier, Matthew D Riemer +4
Large language models are first pre-trained on trillions of tokens and then instruction-tuned or aligned to specific preferences. While pre-training remains out of reach for most r…
Larimar: Large Language Models with Episodic Memory Control
Payel Das, Subhajit Chaudhury, Elliot Nelson +10
Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is one of the most pressing research challenges today. This paper presents Larimar - a novel, br…
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan +3
Protein function annotation is an important yet challenging task in biology. Recent deep learning advancements show significant potential for accurate function prediction by learni…
Structure-Informed Protein Language Model
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan +3
Protein language models are a powerful tool for learning protein representations through pre-training on vast protein sequence datasets. However, traditional protein language model…