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Previous research in multi-document news summarization has typically concentrated on collating information that all sources agree upon.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Estimating the reliability, systematic error and random error of interval data coded by several independent judges
Klaus Krippendorff. 1970 · 1970
Earlier work this paper cites.
Generating summaries of multiple news articles
Kathleen McKeown and Dragomir R. Radev. 1995 · 1995
Earlier work this paper cites.
Generating natural language summaries from multiple on-line sources
Dragomir R. Radev and Kathleen R. McKeown. 1998 · 1998
Earlier work this paper cites.
Information fusion in the context of multi-document summarization
Regina Barzilay, Kathleen R. McKeown, and Michael Elhadad. 1999 · 1999
Earlier work this paper cites.
Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies
Dragomir R. Radev, Hongyan Jing, and Malgorzata Budzikowska. 2000 · 2000
Earlier work this paper cites.
An introduction to duc-2004
Paul Over and James Yen. 2004 · 2004
Earlier work this paper cites.
Overview of duc 2005
Hoa Trang Dang. 2005 · 2005
Earlier work this paper cites.
Overview of the tac 2008 update summarization task
Hoa Trang Dang, Karolina Owczarzak, et al. 2008 · 2008
Earlier work this paper cites.
A scalable global model for summarization
Dan Gillick and Benoit Favre. 2009 · 2009
Earlier work this paper cites.
Opinosis: A graph based approach to abstractive summarization of highly redundant opinions
Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010 · 2010
Earlier work this paper cites.
A class of submodular functions for document summarization
Hui Lin and Jeff Bilmes. 2011 · 2011
Earlier work this paper cites.
Overview of the tac 2011 summarization track: Guided task and aesop task
Karolina Owczarzak and Hoa Trang Dang. 2011 · 2011
Earlier work this paper cites.
Improving the estimation of word importance for news multi-document summarization
Kai Hong and Ani Nenkova. 2014 · 2014
Earlier work this paper cites.
Multi-document abstractive summarization using ILP based multi-sentence compression
Siddhartha Banerjee, Prasenjit Mitra, and Kazunari Sugiyama. 2015 · 2015
Earlier work this paper cites.
The rise of online news aggregators: Consumption and competition
Angela M Lee and Hsiang Iris Chyi. 2015 · 2015
Cited alongside, same era.
Neural summarization by extracting sentences and words
Jianpeng Cheng and Mirella Lapata. 2016 · 2016
Cited alongside, same era.
A general optimization framework for multi-document summarization using genetic algorithms and swarm intelligence
Maxime Peyrard and Judith Eckle-Kohler. 2016 · 2016
Cited alongside, same era.
Towards abstractive multi-document summarization using submodular function-based framework, sentence compression and merging
Yllias Chali, Moin Tanvee, and Mir Tafseer Nayeem. 2017 · 2017
Cited alongside, same era.
Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
Cited alongside, same era.
Discord questions: A computational approach to diversity analysis in news coverage
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs’ka, Xiang Chen, and Caiming Xiong. 2022 · 2022
Later among the works it cites.
CONFIT: Toward faithful dialogue summarization with linguistically-informed contrastive fine-tuning
Xiangru Tang, Arjun Nair, Borui Wang, Bingyao Wang, Jai Desai, Aaron Wade, Haoran Li, Asli Celikyilmaz, Yashar Mehdad, and Dragomir Radev. 2022 · 2022
Later among the works it cites.
Prompted opinion summarization with GPT-3.5
Adithya Bhaskar, Alex Fabbri, and Greg Durrett. 2023 · 2023
Closest in time.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
Closest in time.
Introducing palm 2
Zoubin Ghahramani. 2023 · 2023
Closest in time.
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Ranking sentences for extractive summarization with reinforcement learning
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
Abstractive unsupervised multi-document summarization using paraphrastic sentence fusion
Mir Tafseer Nayeem, Tanvir Ahmed Fuad, and Yllias Chali. 2018 · 2018
Cited alongside, same era.
Towards a neural network approach to abstractive multi-document summarization
Jianmin Zhang, Jiwei Tan, and Xiaojun Wan. 2018 · 2018
Cited alongside, same era.
Auto-hMDS: Automatic construction of a large heterogeneous multilingual multi-document summarization corpus
Markus Zopf. 2018 · 2018
Cited alongside, same era.
Guiding extractive summarization with question-answering rewards
Kristjan Arumae and Fei Liu. 2019 · 2019
Cited alongside, same era.
Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev. 2019 · 2019
Cited alongside, same era.
A large-scale multi-document summarization dataset from the Wikipedia current events portal
Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham, John Glover, and Georgiana Ifrim. 2020 · 2020
Cited alongside, same era.
Kung-Hsiang Huang, Siffi Singh, Xiaofei Ma, Wei Xiao, Feng Nan, Nicholas Dingwall, William Yang Wang, and Kathleen McKeown. 2023 · 2023
Closest in time.
LongEval: Guidelines for human evaluation of faithfulness in long-form summarization
Kalpesh Krishna, Erin Bransom, Bailey Kuehl, Mohit Iyyer, Pradeep Dasigi, Arman Cohan, and Kyle Lo. 2023 · 2023
Closest in time.
Designing and evaluating interfaces that highlight news coverage diversity using discord questions
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs’Ka, Xiang ’Anthony’ Chen, and Caiming Xiong. 2023 · 2023
Closest in time.
How long can open-source llms truly promise on context length?
Dacheng Li, Rulin Shao, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, and Hao Zhang. 2023 · 2023
Closest in time.
Long sequence modeling with xgen: A 7b llm trained on 8k input sequence length
Erik Nijkamp, Tian Xie, Hiroaki Hayashi, Bo Pang, Congying Xia, Chen Xing, Jesse Vig, Semih Yavuz, Philippe Laban, Ben Krause, Senthil Purushwalkam, Tong Niu, Wojciech Kryscinski, Lidiya Murakhovs’ka, Prafulla Kumar Choubey, Alex Fabbri, Ye Liu, Rui Meng, Lifu Tu, Meghana Bhat, Chien-Sheng Wu, Silvio Savarese, Yingbo Zhou, Shafiq Rayhan Joty, and Caiming Xiong. 2023 · 2023
Closest in time.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
Closest in time.
Large language models are not fair evaluators
Peiyi Wang, Lei Li, Liang Chen, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, and Zhifang Sui. 2023 · 2023
Closest in time.
Meta-review generation with checklist-guided iterative introspection
Qi Zeng, Mankeerat Sidhu, Hou Pong Chan, Lu Wang, and Heng Ji. 2023 · 2023
Closest in time.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2023 · 2023
Closest in time.
Amrfact: Enhancing summarization factuality evaluation with amr-driven training data generation
Haoyi Qiu, Kung-Hsiang Huang, Jingnong Qu, and Nanyun Peng. 2024 · 2024
Closest in time.