Papers by Wenyuan Xu
A Boundary Offset Prediction Network for Named Entity Recognition (2023.findings-emnlp)
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| Challenge: | Named entity recognition (NER) is a fundamental task in natural language processing . span-based methods assign entity types to text spans, resulting in imbalanced sample space . |
| Approach: | They propose a method that predicts boundary offsets between candidate and nearest spans . the method integrates entity type and span representations to generate type-aware boundary offset . |
| Outcome: | The proposed method outperforms existing methods on eight widely-used NER datasets. |
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation (2024.emnlp-demo)
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Xuanwang Zhang, Yun-Ze Song, Yidong Wang, Shuyun Tang, Xinfeng Li, Zhengran Zeng, Zhen Wu, Wei Ye, Wenyuan Xu, Yue Zhang, Xinyu Dai, Shikun Zhang, Qingsong Wen
| Challenge: | Existing research on Retrieval Augmented Generation (RAG) does not address the problem of hallucinations and real-time updating of knowledge. |
| Approach: | They propose a modular open-source library to equip LLMs with external knowledge. |
| Outcome: | The proposed approach reduces the need for expensive open-source tools and lacks fair comparisons between novel RAG algorithms. |
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning (2023.findings-emnlp)
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| Challenge: | Experimental results show that noise correction in fine-grained entity typing improves quality of training samples. |
| Approach: | They propose a method that leverages multiple prediction results to correct noisy labels . they integrate prediction results and utilize a differentiated margin to identify inaccurate labels a . |
| Outcome: | The proposed model improves quality of training samples annotated using distant supervision, ChatGPT, and crowdsourcing. |