Papers by Zhengdong Xiao

2 papers
Zero-shot Event Detection Using a Textual Entailment Model as an Enhanced Annotator (2024.lrec-main)

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Challenge: Recent work proposed to use a pre-trained textual entailment model for event detection . but, those methods treated the TE model as a frozen annotator .
Approach: They propose to use TE models to annotate large-scale unlabeled text and annotated data to fine-tune the TE model.
Outcome: The proposed method outperforms baseline methods by 15% on the ACE05 dataset.
Concise and Organized Perception Facilitates Reasoning in Large Language Models (2025.findings-naacl)

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Challenge: Extensive experimental results on several popular logical benchmarks (ProofWriter, PrOntoQA, PrONtoQA-OOD, and FOLIO) and mathematical benchmark (DI-GSM) show that COP significantly outperforms previous state-of-the-art methods.
Approach: They propose a reasoning approach called Concise and Organized Perception (COP) that carefully analyzes the given statements to identify the most pertinent information while eliminating redundancy efficiently.
Outcome: The proposed approach outperforms state-of-the-art methods on several popular logical benchmarks and mathematical benchmarks.

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