11 citations · 23 across the 15 of their papers we have counts for
7 papers · 1 filter
What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search
Xinhao Zhang, Xi Chen, François Portet +1
Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. However, the mechanisms driving these o…
SciTopic: Enhancing Topic Discovery in Scientific Literature through Advanced LLM
Pengjiang Li, Zaitian Wang, Xinhao Zhang +4
Topic discovery in scientific literature provides valuable insights for researchers to identify emerging trends and explore new avenues for investigation, facilitating easier scien…
Distilling Empathy from Large Language Models
Henry J. Xie, Jinghan Zhang, Xinhao Zhang +1
The distillation of knowledge from Large Language Models (LLMs) into Smaller Language Models (SLMs), preserving the capabilities and performance of LLMs while reducing model size,…
Diversity-oriented Data Augmentation with Large Language Models
Zaitian Wang, Jinghan Zhang, Xinhao Zhang +3
Data augmentation is an essential technique in natural language processing (NLP) for enriching training datasets by generating diverse samples. This process is crucial for improvin…
Scoring with Large Language Models: A Study on Measuring Empathy of Responses in Dialogues
Henry J. Xie, Jinghan Zhang, Xinhao Zhang +1
In recent years, Large Language Models (LLMs) have become increasingly more powerful in their ability to complete complex tasks. One such task in which LLMs are often employed is s…
Prototypical Reward Network for Data-Efficient RLHF
Jinghan Zhang, Xiting Wang, Yiqiao Jin +3
The reward model for Reinforcement Learning from Human Feedback (RLHF) has proven effective in fine-tuning Large Language Models (LLMs). Notably, collecting human feedback for RLHF…
Retrieval-Augmented Feature Generation for Domain-Specific Classification
Xinhao Zhang, Jinghan Zhang, Fengran Mo +4
Feature generation can significantly enhance learning outcomes, particularly for tasks with limited data. An effective way to improve feature generation is to expand the current fe…