Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have demonstrated remarkable capabilities in comprehending and analyzing lengthy sequential inputs, owing to their extensive context windows that allow processing millions of tokens in a single forward pass.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
Newsweeder: Learning to filter netnews
Ken Lang. 1995 · 1995
Earlier work this paper cites.
Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.
TextRank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
Earlier work this paper cites.
Practical solutions to the problem of diagonal dominance in kernel document clustering
Derek Greene and Pádraig Cunningham. 2006 · 2006
Earlier work this paper cites.
Application of textrank algorithm for credibility assessment
Bartomiej Balcerzak, Wojciech Jaworski, and Adam Wierzbicki. 2014 · 2014
Earlier work this paper cites.
TLDR: Extreme summarization of scientific documents
Isabel Cachola, Kyle Lo, Arman Cohan, and Daniel Weld. 2020 · 2020
Earlier work this paper cites.
Automatic paper writing based on a rnn and the textrank algorithm
Hei-Chia Wang, Wei-Ching Hsiao, and Sheng-Han Chang. 2020 · 2020
Cited alongside, same era.
A survey on dialogue summarization: Recent advances and new frontiers
Xiachong Feng, Xiaocheng Feng, and Bing Qin. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Cited alongside, same era.
Comparing neural sentence encoders for topic segmentation across domains: not your typical text similarity task
Iacopo Ghinassi, Lin Wang, Chris Newell, and Matthew Purver. 2023 · 2023
Cited alongside, same era.
LLMLingua: Compressing prompts for accelerated inference of large language models
Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang, and Lili Qiu. 2023b · 2023
Cited alongside, same era.
Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al. 2023 · 2023
Later among the works it cites.
Unlimiformer: Long-range transformers with unlimited length input
Amanda Bertsch, Uri Alon, Graham Neubig, and Matthew Gormley. 2024 · 2024
Closest in time.
Gamespot reviews
GameSpot. 2024 · 2024
Closest in time.
In-context autoencoder for context compression in a large language model
Tao Ge, Jing Hu, Lei Wang, Xun Wang, Si-Qing Chen, and Furu Wei. 2024 · 2024
Closest in time.
Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen. 2024 · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dacheng Li, Rulin Shao, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph Gonzalez, Ion Stoica, Xuezhe Ma, and Hao Zhang. 2023 · 2023
Cited alongside, same era.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023a
Cited in the paper.
Daniel Machlab and Rick Battle. 2024 · 2024
Closest in time.
Gpt-3.5-turbo
OpenAI. 2022 · 2024
Closest in time.