When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models | NSF Public Access Repository

skip to main content

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Citation Details

When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models

Award ID(s):: 2346158

PAR ID:: 10575719

Author(s) / Creator(s):: Li, Y; Zhou, Q; Luo, Y; Ma, S; Li, Y; Zheng, H; Hu, X; Yu, Philip S

Publisher / Repository:: Conference on Neural Information Processing Systems (NeurIPS 2024)

Date Published:: 2024-12-11

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript
Conference Paper:
The DOI is not currently available.