Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees

21 September 2022

Papers citing "Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees"

8 / 8 papers shown

Title
ADaPT: As-Needed Decomposition and Planning with Language Models Archiki Prasad Alexander Koller Mareike Hartmann Peter Clark Ashish Sabharwal Mohit Bansal Tushar Khot LM&Ro 21 74 0 08 Nov 2023
Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model Jacob Eisenstein D. Andor Bernd Bohnet Michael Collins David M. Mimno LRM 187 24 0 05 Oct 2022
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 297 3,217 0 21 Mar 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
Explaining Answers with Entailment Trees Bhavana Dalvi Peter Alexander Jansen Oyvind Tafjord Zhengnan Xie Hannah Smith Leighanna Pipatanangkura Peter Clark ReLM FAtt LRM 237 184 0 17 Apr 2021
Text Summarization with Pretrained Encoders Yang Liu Mirella Lapata MILM 254 1,417 0 22 Aug 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 170 3,504 0 10 Jun 2015