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LLMs and RAG systems are now capable of handling millions of input tokens or more.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Earlier work this paper cites.
ELI5: Long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 2019
Earlier work this paper cites.
SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Re-evaluating evaluation in text summarization
Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, and Graham Neubig. 2020 · 2020
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Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020 · 2020
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The summary loop: Learning to write abstractive summaries without examples
Philippe Laban, Andrew Hsi, John Canny, and Marti A Hearst. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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QMSum: A new benchmark for query-based multi-domain meeting summarization
Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, and Dragomir Radev. 2021 · 2021
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DialSummEval: Revisiting summarization evaluation for dialogues
Mingqi Gao and Xiaojun Wan. 2022 · 2022
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Discord questions: A computational approach to diversity analysis in news coverage
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs’ka, Xiang Chen, and Caiming Xiong. 2022b · 2022
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Revisiting the gold standard: Grounding summarization evaluation with robust human evaluation
Yixin Liu, Alexander R Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, et al. 2022 · 2022
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Teaching language models to support answers with verified quotes
Jacob Menick, Maja Trebacz, Vladimir Mikulik, John Aslanides, Francis Song, Martin Chadwick, Mia Glaese, Susannah Young, Lucy Campbell-Gillingham, Geoffrey Irving, et al. 2022 · 2022
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Exploring neural models for query-focused summarization
Jesse Vig, Alexander Fabbri, Wojciech Kryscinski, Chien-Sheng Wu, and Wenhao Liu. 2022 · 2022
Cited alongside, same era.
L-eval: Instituting standardized evaluation for long context language models
Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, and Xipeng Qiu. 2023 · 2023
Cited alongside, same era.
Longbench: A bilingual, multitask benchmark for long context understanding
Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, et al. 2023 · 2023
Cited alongside, same era.
Booookscore: A systematic exploration of book-length summarization in the era of llms
Yapei Chang, Kyle Lo, Tanya Goyal, and Mohit Iyyer. 2023 · 2023
Cited alongside, same era.
Menli: Robust evaluation metrics from natural language inference
Automatic evaluation of attribution by large language models
Xiang Yue, Boshi Wang, Ziru Chen, Kai Zhang, Yu Su, and Huan Sun. 2023 · 2023
Later among the works it cites.
Alignscore: Evaluating factual consistency with a unified alignment function
Yuheng Zha, Yichi Yang, Ruichen Li, and Zhiting Hu. 2023 · 2023
Later among the works it cites.
Llama 3 model card
AI@Meta. 2024 · 2024
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Benchmarking large language models in complex question answering attribution using knowledge graphs
Nan Hu, Jiaoyan Chen, Yike Wu, Guilin Qi, Sheng Bi, Tongtong Wu, and Jeff Z Pan. 2024 · 2024
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Introducing rerank 3: The next generation of search relevance
Cohere Inc. 2024 · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Yanran Chen and Steffen Eger. 2023 · 2023
Cited alongside, same era.
Seahorse: A multilingual, multifaceted dataset for summarization evaluation
Elizabeth Clark, Shruti Rijhwani, Sebastian Gehrmann, Joshua Maynez, Roee Aharoni, Vitaly Nikolaev, Thibault Sellam, Aditya Siddhant, Dipanjan Das, and Ankur P Parikh. 2023 · 2023
Cited alongside, same era.
Zican Dong, Tianyi Tang, Junyi Li, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
Cited alongside, same era.
Kung-Hsiang Huang, Philippe Laban, Alexander R Fabbri, Prafulla Kumar Choubey, Shafiq Joty, Caiming Xiong, and Chien-Sheng Wu. 2023 · 2023
Cited alongside, same era.
Hagrid: A human-llm collaborative dataset for generative information-seeking with attribution
Ehsan Kamalloo, Aref Jafari, Xinyu Zhang, Nandan Thakur, and Jimmy Lin. 2023 · 2023
Cited alongside, same era.
Needleinahaystack
Gregory Kamradt. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Wai-Chung Kwan, Xingshan Zeng, Yufei Wang, Yusen Sun, Liangyou Li, Lifeng Shang, Qun Liu, and Kam-Fai Wong. 2023 · 2023
Cited alongside, same era.
Yekyung Kim, Yapei Chang, Marzena Karpinska, Aparna Garimella, Varun Manjunatha, Kyle Lo, Tanya Goyal, and Mohit Iyyer. 2024 · 2024
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In search of needles in a 10m haystack: Recurrent memory finds what llms miss
Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Dmitry Sorokin, Artyom Sorokin, and Mikhail Burtsev. 2024 · 2024
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Multi-needle in a haystack
LangChain. 2024 · 2024
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Attributionbench: How hard is automatic attribution evaluation?
Yifei Li, Xiang Yue, Zeyi Liao, and Huan Sun. 2024 · 2024
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Llm in-context recall is prompt dependent
Daniel Machlab and Rick Battle. 2024 · 2024
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Xl bench: A benchmark for extremely long context understanding with long-range dependencies
Xuanfan Ni, Hengyi Cai, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, and Piji Li. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al. 2024 · 2024
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Milebench: Benchmarking mllms in long context
Dingjie Song, Shunian Chen, Guiming Hardy Chen, Fei Yu, Xiang Wan, and Benyou Wang. 2024 · 2024
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Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. 2024 · 2024
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Minicheck: Efficient fact-checking of llms on grounding documents
Liyan Tang, Philippe Laban, and Greg Durrett. 2024 · 2024
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Longembed: Extending embedding models for long context retrieval
Dawei Zhu, Liang Wang, Nan Yang, Yifan Song, Wenhao Wu, Furu Wei, and Sujian Li. 2024 · 2024
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