1 citations · 1 across the 3 of their papers we have counts for
5 papers
Quantile-Optimal Policy Learning under Unmeasured Confounding
Zhongren Chen, Siyu Chen, Zhengling Qi +2
We study quantile-optimal policy learning where the goal is to find a policy whose reward distribution has the largest -quantile for some . We focus on the offline…
An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds
Siyu Chen, Theodor Misiakiewicz, Ilias Zadik +1
Bandeira et al. (2022) introduced the Franz-Parisi (FP) criterion for characterizing the computational hard phases in statistical detection problems. The FP criterion, based on an…
Penrose Tiled Low-Rank Compression and Section-Wise Q&A Fine-Tuning: A General Framework for Domain-Specific Large Language Model Adaptation
Chuan-Wei Kuo, Siyu Chen, Chenqi Yan +1
Large language models (LLMs) hold great promise for specialized scientific domains such as materials science, yet adapting them efficiently and accurately to domain-specific knowle…
DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization
Xuefeng Liu, Songhao Jiang, Siyu Chen +4
Finetuning a Large Language Model (LLM) is crucial for generating results towards specific objectives. This research delves into the realm of drug optimization and introduce a nove…
DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration
Sizhe Liu, Yizhou Lu, Siyu Chen +4
Recent progress in Large Language Models (LLMs) has drawn attention to their potential for accelerating drug discovery. However, a central problem remains: translating theoretical…