2 citations · 3 across the 6 of their papers we have counts for
6 papers
Can Decision Trees Teach Large Language Models? Distilling Verbalized Knowledge for Molecular Property Prediction
Khiem Le, Sreejata Dey, Marcos Martínez Galindo +4
Molecular Property Prediction (MPP) is a fundamental problem in drug discovery that has recently attracted growing attention. Large Language Models (LLMs), known for their impressi…
Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models
Khiem Le, Phuc Nguyen, Youssef Mroueh +4
Group Relative Policy Optimization (GRPO) has become the dominant method for reinforcement learning with verifiable rewards in large language models, but it suffers from two critic…
FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE
Khiem Le, Tuan Tran, Ting Hua +1
Existing resource-adaptive LoRA federated fine-tuning methods enable clients to fine-tune models using compressed versions of global LoRA matrices, in order to accommodate various…
Bridging the AI Adoption Gap: Designing an Interactive Pedagogical Agent for Higher Education Instructors
Si Chen, Reid Metoyer, Khiem Le +6
Instructors play a pivotal role in integrating AI into education, yet their adoption of AI-powered tools remains inconsistent. Despite this, limited research explores how to design…
Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data
Haoyan Yang, Khiem Le, Ting Hua +7
Although LLMs have achieved significant success, their reliance on large volumes of human-annotated data has limited their potential for further scaling. In this situation, utilizi…
MolX: Enhancing Large Language Models for Molecular Understanding With A Multi-Modal Extension
Khiem Le, Zhichun Guo, Kaiwen Dong +8
Large Language Models (LLMs) with their strong task-handling capabilities have shown remarkable advancements across a spectrum of fields, moving beyond natural language understandi…