Rethinking STS and NLI in Large Language Models

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Rethinking STS and NLI in Large Language Models

16 September 2023

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Papers citing "Rethinking STS and NLI in Large Language Models"

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Title
How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks Xuanting Chen Junjie Ye Can Zu Nuo Xu Rui Zheng Minlong Peng Jie Zhou Tao Gui Qi Zhang Xuanjing Huang AI4MH ELM 61 83 0 01 Mar 2023
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT Qihuang Zhong Liang Ding Juhua Liu Bo Du Dacheng Tao AI4MH 108 245 0 19 Feb 2023
Language Models (Mostly) Know What They Know Saurav Kadavath Tom Conerly Amanda Askell T. Henighan Dawn Drain ... Nicholas Joseph Benjamin Mann Sam McCandlish C. Olah Jared Kaplan ELM 122 830 0 11 Jul 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 823 9,644 0 28 Jan 2022
What Can We Learn from Collective Human Opinions on Natural Language Inference Data? Yixin Nie Xiang Zhou Joey Tianyi Zhou 86 138 0 07 Oct 2020
Lessons from Natural Language Inference in the Clinical Domain Alexey Romanov Chaitanya P. Shivade LM&MA 80 272 0 21 Aug 2018
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 524 4,494 0 18 Apr 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,719 0 15 Mar 2017
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 324 4,293 0 21 Aug 2015