Papers by Chengyu Gu
Text Grafting: Near-Distribution Weak Supervision for Minority Classes in Text Classification (2024.emnlp-main)
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| Challenge: | Recent work generates pseudo labels by mining texts similar to the class names from the raw corpus, but there is a high risk that LLMs cannot generate in-distribution data, leading to ungeneralizable classifiers. |
| Approach: | They propose to use LLMs to generate pseudo labels by mining masked templates from corpus . they then use state-of-the-art LLM to synthesize near-distribution texts falling into minority classes . |
| Outcome: | The proposed framework improves on the previous methods for extremely weak-supervised text classification. |
TracSum: A New Benchmark for Aspect-Based Summarization with Sentence-Level Traceability in Medical Domain (2025.emnlp-main)
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| Challenge: | Existing evidence-based summarization tasks require tracing source evidence to assess their accuracy. |
| Approach: | They propose a benchmark for traceable, aspect-based summarization that pairs summaries with sentence-level citations to enable users to trace back to the original context. |
| Outcome: | The proposed benchmark can be used to evaluate document summarization with LLMs and human evaluations. |