Papers by Weicheng Ren
Self-Para-Consistency: Improving Reasoning Tasks at Low Cost for Large Language Models (2024.findings-acl)
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| Challenge: | Recent studies have shown that self-consistency decoding can improve performance for complex reasoning tasks with large language models. |
| Approach: | They propose a self-consistency decoding strategy that generates multiple paraphrases for each test question and then generates reasoning paths for the original and all the paraphrased questions based on greedy decoding. |
| Outcome: | The proposed strategy reduces the sampling number and improves performance on complex reasoning tasks. |
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction (2024.acl-long)
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Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren, Wenxuan Liu, Miao Su, Yucan Guo, Yantao Liu, Lixiang Lixiang, Zhilei Hu, Long Bai, Wei Li, Yidan Liu, Pan Yang, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
| Challenge: | None. None.. None! |
| Approach: | None. None.. None! |
| Outcome: | None. None. No. : |
Nested Event Extraction upon Pivot Element Recognition (2024.lrec-main)
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Weicheng Ren, Zixuan Li, Xiaolong Jin, Long Bai, Miao Su, Yantao Liu, Saiping Guan, Jiafeng Guo, Xueqi Cheng
| Challenge: | Nested Event Extraction (NEE) aims to extract complex event structures where an event contains other events as its arguments recursively. |
| Approach: | They propose a new model that extracts nested events mainly based on recognizing PEs. |
| Outcome: | The proposed model can extract nested events based on recognizing PEs . it incorporates information from both event types and argument roles to improve performance . |