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Hefan Zhang

5 accepted papers

2025

A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labelling

EMNLP 2025

Rhetorical strategies are central to persuasive communication, from political discourse and marketing to legal argumentation. However, analysis of rhetorical strategies has been limited by reliance on human annotation, which is costly, inconsistent, difficult to scale. Their associated datasets are

Cited by 0SourcePDFScholar
2025

Communication Makes Perfect: Persuasion Dataset Construction via Multi-LLM Communication

NAACL 2025long

Large Language Models (LLMs) have shown proficiency in generating persuasive dialogue, yet concerns about the fluency and sophistication of their outputs persist. This paper presents a multi-LLM communication framework designed to enhance the generation of persuasive data automatically. This framewo…

Cited by 1SourcePDFScholar
2025

Enhancing LLM-Based Persuasion Simulations with Cultural and Speaker-Specific Information

EMNLP 2025

Large language models (LLMs) have been used to synthesize persuasive dialogues for studying persuasive behavior. However, existing approaches often suffer from issues such as stance oscillation and low informativeness. To address these challenges, we propose reinforced instructional prompting, a met

Cited by 0SourcePDFScholar
2025

Recontextualizing Revitalization: A Mixed Media Approach to Reviving the Nüshu Language

EMNLP 2025

Nüshu is an endangered language from Jiangyong County, China, and the world’s only known writing system created and used exclusively by women. Recent Natural Language Processing (NLP) work has digitized small Nüshu-Chinese corpora, but the script remains computationally inaccessible due to its handw

Cited by 0SourcePDFScholar
2023

Improving Syntactic Probing Correctness and Robustness with Control Tasks

ACL 2023short

Syntactic probing methods have been used to examine whether and how pre-trained language models (PLMs) encode syntactic features. However, the probing methods are usually biased by the PLMs’ memorization of common word co-occurrences, even if they do not form syntactic relations. This paper presents…

Cited by 2SourcePDFScholar