Papers by Jianhua Dai

2 papers
Mitigating Demonstration Bias through Global Coevolutionary Reasoning (2025.findings-acl)

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Challenge: Existing methods for chain-of-thought prompting rely on manual demonstrations . experimental results show that GCR outperforms baseline methods without performance degradation .
Approach: They propose a method that uses random samples to generate demonstrations in zero-shot settings.
Outcome: The proposed method outperforms baseline methods on ten datasets without demonstration bias.
CoELM: Construction-Enhanced Language Modeling (2024.acl-long)

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Challenge: Recent studies show that integrating constructional information can improve the performance of pre-trained language models.
Approach: They propose a construction-Enhanced language model that embeds constructional semantics into language models for natural language generation.
Outcome: The proposed model outperforms existing models on various benchmarks.

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