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Look at the Text: Instruction-Tuned Language Models are More Robust
  Multiple Choice Selectors than You Think

Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think

12 April 2024
Xinpeng Wang
Chengzhi Hu
Bolei Ma
Paul Röttger
Barbara Plank
    OOD
ArXivPDFHTML

Papers citing "Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think"

4 / 4 papers shown
Title
The Digital Cybersecurity Expert: How Far Have We Come?
The Digital Cybersecurity Expert: How Far Have We Come?
Dawei Wang
Geng Zhou
Xianglong Li
Yu Bai
Li Chen
Ting Qin
Jian Sun
D. Li
ELM
62
0
0
16 Apr 2025
Are You Doubtful? Oh, It Might Be Difficult Then! Exploring the Use of Model Uncertainty for Question Difficulty Estimation
Are You Doubtful? Oh, It Might Be Difficult Then! Exploring the Use of Model Uncertainty for Question Difficulty Estimation
Leonidas Zotos
H. Rijn
Malvina Nissim
75
0
0
16 Dec 2024
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang
Jason W. Wei
Dale Schuurmans
Quoc Le
Ed H. Chi
Sharan Narang
Aakanksha Chowdhery
Denny Zhou
ReLM
BDL
LRM
AI4CE
314
3,248
0
21 Mar 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
319
11,953
0
04 Mar 2022
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