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Li Xie

2 accepted papers

2025

Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy

COLING 2025main

In recent years, the use of large language models (LLMs) for text classification has attracted widespread attention. Despite this, the classification accuracy of LLMs has not yet universally surpassed that of smaller models. LLMs can enhance their performance in text classification through fine-tuni…

Cited by 1SourcePDFScholar
2025

GTA: Supervised-Guided Reinforcement Learning for Text Classification with Large Language Models

EMNLP 2025

In natural language processing (NLP) tasks, pure reinforcement learning fine-tuning methods often suffer from inefficient exploration and slow convergence; while supervised fine-tuning (SFT) methods, although efficient in training, have limited performance ceiling and less solid theoretical foundati

Cited by 0SourcePDFScholar