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Anchen Li

2 accepted papers

2026

Steering Large Language Models through the DMTA Cycle: Structure-Based Drug Design via Knowledge-Driven Bi-Level Thompson Sampling

ICML 2026poster

Structure-based drug design (SBDD) can be effectively realized through an iterative refinement via the Design-Make-Test-Analyze (DMTA) cycle, which is a common workflow used by human experts. However, most LLMs function as one-shot generators that lack feedback mechanisms, leaving the DMTA loop disc…

Cited by 0SourceScholar
2022

A Probabilistic Graphical Model Based on Neural-Symbolic Reasoning for Visual Relationship Detection

CVPR 2022poster

This paper aims to leverage symbolic knowledge to improve the performance and interpretability of the Visual Relationship Detection (VRD) models. Existing VRD methods based on deep learning suffer from the problems of poor performance on insufficient labeled examples and lack of interpretability. To…

Cited by 28PDFScholar