REVIEW 2 cited by
"Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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.
Forward citations
Cited by 2 Pith papers
-
Pragmatic Theories Enhance Understanding of Implied Meanings in LLMs
Zero-shot prompts that summarize Gricean pragmatics or Relevance Theory improve LLM accuracy on PRAGMEGA implied-meaning questions by up to 9.6 percentage points; just naming the theory helps larger models.
-
They want to pretend not to understand: The Limits of Current LLMs in Interpreting Implicit Content of Political Discourse
Even the best tested model, GPT4o-mini, falls more than 20 accuracy points short of the estimated human ceiling on a multiple-choice test and is fully correct in only about one-fourth of open-ended explanations.
Discussion (0). Sign in to comment.