Papers by Hangxiao Zhu

2 papers
Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations (2023.emnlp-main)

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Challenge: Recent studies have explored using large language models to generate synthetic datasets . however, the effectiveness of the LLM-generated synthetic data is inconsistent across different classification tasks.
Approach: They propose to use large language models to generate synthetic datasets to better understand factors that moderate the effectiveness of LLM-generated synthetic data.
Outcome: The results show that subjectivity is negatively associated with the performance of the model trained on synthetic data.
SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction (2026.findings-acl)

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Challenge: Prior work on scientific impact prediction has focused on citation counts and its variants, leaving limited evaluation of models’ capability to reason about other dimensions.
Approach: They propose a large-scale, multi-dimensional benchmark for scientific impact prediction spanning 19 fields.
Outcome: The proposed model outperforms larger models and close-source models in a wide range of fields and measures of scientific impact across 19 fields.

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