arXiv:2305.13826
"Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures
원문 초록
Conversational implicatures are pragmatic inferences that require listeners to deduce the intended meaning conveyed by a speaker from their explicit utterances. Although such inferential reasoning is fundamental to human communication, recent research indicates that large language models struggle to comprehend these implicatures as effectively as the average human. This paper demonstrates that by incorporating Grice's Four Maxims into the model through chain-of-thought prompting, we can significantly enhance its performance, surpassing even the average human performance on this task.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Do Large Language Models Understand Conversational Implicature -- A case study with a chinese sitcom
Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics
Interactive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discourse
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
Can Vision-Language Models Infer Speaker's Ignorance? The Role of Visual and Linguistic Cues
토론
이 논문과 연결된 포럼 글이 아직 없습니다.