Large Language Models are In-context Teachers for Knowledge Reasoning

12 November 2023

Papers citing "Large Language Models are In-context Teachers for Knowledge Reasoning"

7 / 7 papers shown

Title
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Lokesh Nagalapatti Chun-Liang Li Chih-Kuan Yeh Hootan Nakhost Yasuhisa Fujii Alexander Ratner Ranjay Krishna Chen-Yu Lee Tomas Pfister ALM 204 498 0 03 May 2023
Complexity-Based Prompting for Multi-Step Reasoning Yao Fu Hao-Chun Peng Ashish Sabharwal Peter Clark Tushar Khot ReLM LRM 158 411 0 03 Oct 2022
What Makes Pre-trained Language Models Better Zero-shot Learners? Jinghui Lu Dongsheng Zhu Weidong Han Rui Zhao Brian Mac Namee Fei Tan 34 21 0 30 Sep 2022
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Pan Lu Swaroop Mishra Tony Xia Liang Qiu Kai-Wei Chang Song-Chun Zhu Oyvind Tafjord Peter Clark A. Kalyan ELM ReLM LRM 207 1,089 0 20 Sep 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 4,048 0 24 May 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 315 8,261 0 28 Jan 2022
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies Mor Geva Daniel Khashabi Elad Segal Tushar Khot Dan Roth Jonathan Berant RALM 245 671 0 06 Jan 2021