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It's Not Easy Being Wrong: Large Language Models Struggle with Process
  of Elimination Reasoning
v1v2v3 (latest)

It's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning

Annual Meeting of the Association for Computational Linguistics (ACL), 2023
13 November 2023
Nishant Balepur
Shramay Palta
Rachel Rudinger
    LRM
ArXiv (abs)PDFHTML

Papers citing "It's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning"

3 / 3 papers shown
Title
Can Competition Enhance the Proficiency of Agents Powered by Large Language Models in the Realm of News-driven Time Series Forecasting?
Can Competition Enhance the Proficiency of Agents Powered by Large Language Models in the Realm of News-driven Time Series Forecasting?
Yuxuan Zhang
Yangyang Feng
Daifeng Li
Kexin Zhang
Junlan Chen
Bowen Deng
LLMAGAI4TS
176
1
0
14 Apr 2025
Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More
Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More MoreAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Arvid Frydenlund
LRM
458
2
0
13 Mar 2025
Option-ID Based Elimination For Multiple Choice Questions
Option-ID Based Elimination For Multiple Choice Questions
Zhenhao Zhu
Bulou Liu
Jiaxin Mao
Wenshu Fan
259
1
0
25 Jan 2025
1