APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning

29 August 2018

Papers citing "APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning"

20 / 20 papers shown

Title
Advances in Preference-based Reinforcement Learning: A Review Youssef Abdelkareem Shady Shehata Fakhri Karray OffRL 51 9 0 21 Aug 2024
The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values Hannah Rose Kirk Andrew M. Bean Bertie Vidgen Paul Röttger Scott A. Hale ALM 21 42 0 11 Oct 2023
Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering Hai Ye Qizhe Xie Hwee Tou Ng 42 8 0 11 Jun 2023
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation Patrick Fernandes Aman Madaan Emmy Liu António Farinhas Pedro Henrique Martins ... José G. C. de Souza Shuyan Zhou Tongshuang Wu Graham Neubig André F. T. Martins ALM 117 56 0 01 May 2023
Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback Hannah Rose Kirk Bertie Vidgen Paul Röttger Scott A. Hale 41 100 0 09 Mar 2023
Quark: Controllable Text Generation with Reinforced Unlearning Ximing Lu Sean Welleck Jack Hessel Liwei Jiang Lianhui Qin Peter West Prithviraj Ammanabrolu Yejin Choi MU 66 206 0 26 May 2022
Make The Most of Prior Data: A Solution for Interactive Text Summarization with Preference Feedback Duy-Hung Nguyen Nguyen-Viet-Dung Nghiem Bao-Sinh Nguyen Dung Tien Le Shahab Sabahi Minh Le Nguyen Hung Le 29 13 0 12 Apr 2022
NLPGym -- A toolkit for evaluating RL agents on Natural Language Processing Tasks Rajkumar Ramamurthy R. Sifa Christian Bauckhage 21 5 0 16 Nov 2020
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation Yuning Mao Xiang Ren Heng Ji Jiawei Han HILM 125 38 0 24 Oct 2020
KLearn: Background Knowledge Inference from Summarization Data Maxime Peyrard Robert West 19 3 0 13 Oct 2020
Empowering Active Learning to Jointly Optimize System and User Demands Ji-Ung Lee Christian M. Meyer Iryna Gurevych 11 11 0 09 May 2020
SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization Yang Gao Wei-Ye Zhao Steffen Eger ELM 24 124 0 07 May 2020
An Imitation Game for Learning Semantic Parsers from User Interaction Ziyu Yao Yiqi Tang Wen-tau Yih Huan Sun Yu-Chuan Su 28 34 0 02 May 2020
Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model Hamid Reza Mohammadi S. H. Khasteh Tahereh Firoozi Taha Samavati 24 20 0 12 Dec 2019
Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation Edwin Simpson Yang Gao Iryna Gurevych BDL 13 10 0 22 Nov 2019
Better Rewards Yield Better Summaries: Learning to Summarise Without References F. Böhm Yang Gao Christian M. Meyer Ori Shapira Ido Dagan Iryna Gurevych 25 107 0 03 Sep 2019
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation Yang Gao Christian M. Meyer Mohsen Mesgar Iryna Gurevych 20 22 0 30 Jul 2019
Preference-based Interactive Multi-Document Summarisation Yang Gao Christian M. Meyer Iryna Gurevych 14 27 0 07 Jun 2019
Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation Ori Shapira David Gabay Yang Gao H. Ronen Ramakanth Pasunuru Joey Tianyi Zhou Yael Amsterdamer Ido Dagan 19 60 0 11 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 39 626 0 29 Mar 2019