Fetching the paper…
Reading the bibliography…
The context window of large language models (LLMs) has been extended significantly in recent years.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
Earlier work this paper cites.
Improving neural language models with a continuous cache
Edouard Grave, Armand Joulin, and Nicolas Usunier · 2017
Earlier work this paper cites.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer · 2017
Earlier work this paper cites.
Attention is all you need
A Vaswani · 2017
Earlier work this paper cites.
Search engine guided neural machine translation
Jiatao Gu, Yong Wang, Kyunghyun Cho, and Victor OK Li · 2018
Earlier work this paper cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D Manning · 2018
Earlier work this paper cites.
Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov · 2019
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Earlier work this paper cites.
Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
Earlier work this paper cites.
Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang · 2020
Earlier work this paper cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Neural machine translation with monolingual translation memory
Deng Cai, Yan Wang, Huayang Li, Wai Lam, and Lemao Liu · 2021
Earlier work this paper cites.
Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, and Jonathan Berant · 2021
Earlier work this paper cites.
Autoregressive search engines: Generating substrings as document identifiers
Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis, Scott Yih, Sebastian Riedel, and Fabio Petroni · 2022
Earlier work this paper cites.
Overcoming a theoretical limitation of self-attention
David Chiang and Peter Cholak · 2022
Earlier work this paper cites.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
Large dual encoders are generalizable retrievers
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernandez Abrego, Ji Ma, Vincent Zhao, Yi Luan, Keith Hall, Ming-Wei Chang, et al · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Cited alongside, same era.
Train short, test long: Attention with linear biases enables input length extrapolation
Ofir Press, Noah Smith, and Mike Lewis · 2022
Cited alongside, same era.
Transformer memory as a differentiable search index
Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, et al · 2022
Cited alongside, same era.
Galactica: A large language model for science
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez, and Robert Stojnic · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
System 2 attention (is something you might need too)
Jason Weston and Sainbayar Sukhbaatar · 2023
Later among the works it cites.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao · 2023
Later among the works it cites.
Self-RAG: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi · 2024
Closest in time.
In-context autoencoder for context compression in a large language model
Tao Ge, Hu Jing, Lei Wang, Xun Wang, Si-Qing Chen, and Furu Wei · 2024
Closest in time.
Ruler: What’s the real context size of your long-context language models?
Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, Shantanu Acharya, Dima Rekesh, Fei Jia, and Boris Ginsburg · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Extending context window of large language models via positional interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, and Yuandong Tian · 2023
Cited alongside, same era.
Adapting language models to compress contexts
Alexis Chevalier, Alexander Wettig, Anirudh Ajith, and Danqi Chen · 2023
Cited alongside, same era.
Enabling large language models to generate text with citations
Tianyu Gao, Howard Yen, Jiatong Yu, and Danqi Chen · 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 · 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
Cited alongside, same era.
Needle In A Haystack - pressure testing LLMs
Gregory Kamradt · 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
Cited alongside, same era.
LongLLMLingua: Accelerating and enhancing LLMs in long context scenarios via prompt compression
Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, and Lili Qiu · 2024
Closest in time.
One thousand and one pairs: A ”novel” challenge for long-context language models, 2024
Marzena Karpinska, Katherine Thai, Kyle Lo, Tanya Goyal, and Mohit Iyyer · 2024
Closest in time.
Source-aware training enables knowledge attribution in language models
Muhammad Khalifa, David Wadden, Emma Strubell, Honglak Lee, Lu Wang, Iz Beltagy, and Hao Peng · 2024
Closest in time.
Babilong: Testing the limits of llms with long context reasoning-in-a-haystack
Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Sorokin, and Mikhail Burtsev · 2024
Closest in time.
Can long-context language models subsume retrieval, rag, sql, and more?
Jinhyuk Lee, Anthony Chen, Zhuyun Dai, Dheeru Dua, Devendra Singh Sachan, Michael Boratko, Yi Luan, Sébastien MR Arnold, Vincent Perot, Siddharth Dalmia, et al · 2024
Closest in time.
Lost in the Middle: How Language Models Use Long Contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang · 2024
Closest in time.
Base of rope bounds context length
Xin Men, Mingyu Xu, Bingning Wang, Qingyu Zhang, Hongyu Lin, Xianpei Han, and Weipeng Chen · 2024
Closest in time.
Leave no context behind: Efficient infinite context transformers with infini-attention
Tsendsuren Munkhdalai, Manaal Faruqui, and Siddharth Gopal · 2024
Closest in time.
Replug: Retrieval-augmented black-box language models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Richard James, Mike Lewis, Luke Zettlemoyer, and Wen-tau Yih · 2024
Closest in time.
Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis · 2024
Closest in time.
RECOMP: Improving retrieval-augmented LMs with context compression and selective augmentation
Fangyuan Xu, Weijia Shi, and Eunsol Choi · 2024
Closest in time.
Effective large language model adaptation for improved grounding and citation generation
Xi Ye, Ruoxi Sun, Sercan Arik, and Tomas Pfister · 2024
Closest in time.
Long-context language modeling with parallel context encoding
Howard Yen, Tianyu Gao, and Danqi Chen · 2024
Closest in time.
∞ \infty Bench: Extending long context evaluation beyond 100k tokens
Xinrong Zhang, Yingfa Chen, Shengding Hu, Zihang Xu, Junhao Chen, Moo Hao, Xu Han, Zhen Thai, Shuo Wang, Zhiyuan Liu, et al · 2024
Closest in time.