Papers by Junhao Lu

2 papers
SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have demonstrated strong performance across various NLP tasks, but their effectiveness in ECI remains limited due to biases in causal reasoning.
Approach: They propose a structural example retrieval framework that leverages LLMs’ few-shot learning capabilities to help LLM models in ECI.
Outcome: The proposed framework leverages LLMs’ few-shot learning capabilities to guide LLM models in causal reasoning, mitigating bias and improving accuracy.
Handling Missing Entities in Zero-Shot Named Entity Recognition: Integrated Recall and Retrieval Augmentation (2025.naacl-long)

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Challenge: Zero-shot Named Entity Recognition (ZS-NER) aims to recognize entities in unseen domains without specific annotated data.
Approach: They propose a novel two-stage framework leveraging large language model techniques to improve the ZS-NER’s recall rate.
Outcome: The proposed framework improves the ZS-NER’s recall rate and accuracy by incorporating a large language model.

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