DOLOMITES: Domain-Specific Long-Form Methodical Tasks

Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel

J Peter Kincaid, Robert P Fishburne Jr, Richard L Rogers, and Brad S Chissom. 1975 · 1975

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ROUGE: A package for automatic evaluation of summaries

Chin-Yew Lin. 2004 · 2004

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An overview of the bioasq large-scale biomedical semantic indexing and question answering competition

George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, et al. 2015 · 2015

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How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation

Chia-Wei Liu, Ryan Lowe, Iulian Serban, Mike Noseworthy, Laurent Charlin, and Joelle Pineau. 2016 · 2016

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Ms marco: A human generated machine reading comprehension dataset

Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016 · 2016

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Why we need new evaluation metrics for NLG

Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, and Verena Rieser. 2017 · 2017

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The limits of automatic summarisation according to ROUGE

Natalie Schluter. 2017 · 2017

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emrQA: A large corpus for question answering on electronic medical records

Anusri Pampari, Preethi Raghavan, Jennifer Liang, and Jian Peng. 2018 · 2018

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Pubmedqa: A dataset for biomedical research question answering

Original

Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019

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Natural questions: A benchmark for question answering research

Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019

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How novelists use generative language models: An exploratory user study

Alex Calderwood, Vivian Qiu, Katy Ilonka Gero, and Lydia B Chilton. 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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BLEURT: Learning robust metrics for text generation

Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020

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Documenting large webtext corpora: A case study on the colossal clean crawled corpus

Jesse Dodge, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell, and Matt Gardner. 2021 · 2021

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Wikiasp: A dataset for multi-domain aspect-based summarization

Hiroaki Hayashi, Prashant Budania, Peng Wang, Chris Ackerson, Raj Neervannan, and Graham Neubig. 2021 · 2021

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Measuring massive multitask language understanding

Original

Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021

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What disease does this patient have? a large-scale open domain question answering dataset from medical exams

Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2021 · 2021

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Hurdles to progress in long-form question answering

Kalpesh Krishna, Aurko Roy, and Mohit Iyyer. 2021 · 2021

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Natural language processing in legal tech

Jens Frankenreiter and Julian Nyarko. 2022 · 2022

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Sparks: Inspiration for science writing using language models

Katy Ilonka Gero, Vivian Liu, and Lydia Chilton. 2022 · 2022

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TRUE: Re-evaluating factual consistency evaluation

Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022 · 2022

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Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities

Mina Lee, Percy Liang, and Qian Yang. 2022 · 2022

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Multi-lexsum: Real-world summaries of civil rights lawsuits at multiple granularities

Zejiang Shen, Kyle Lo, Lauren Yu, Nathan Dahlberg, Margo Schlanger, and Doug Downey. 2022 · 2022

Cited alongside, same era.

Science in the age of large language models

Abeba Birhane, Atoosa Kasirzadeh, David Leslie, and Sandra Wachter. 2023 · 2023

Cited alongside, same era.

Can large language models be an alternative to human evaluations?

Cheng-Han Chiang and Hung-yi Lee. 2023 · 2023

Cited alongside, same era.

Palm: Scaling language modeling with pathways

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023 · 2023

Cited alongside, same era.

Navigating the jagged technological frontier: Field experimental evidence of the effects of ai on knowledge worker productivity and quality

Fabrizio Dell’Acqua, Edward McFowland, Ethan R Mollick, Hila Lifshitz-Assaf, Katherine Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R Lakhani. 2023 · 2023

Cited alongside, same era.

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, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023

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The claude 3 model family: Opus, sonnet, haiku

Anthropic · 2024

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Introducing Command R+: A Scalable LLM Built for Business

Cohere. 2024 · 2024

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What’s in my big data?

Yanai Elazar, Akshita Bhagia, Ian Helgi Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah A. Smith, and Jesse Dodge. 2024 · 2024

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Gpts are gpts: Labor market impact potential of llms

Tyna Eloundou, Sam Manning, Pamela Mishkin, and Daniel Rock. 2024 · 2024

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Learning to plan and generate text with citations

Constanza Fierro, Reinald Kim Amplayo, Fantine Huot, Nicola De Cao, Joshua Maynez, Shashi Narayan, and Mirella Lapata. 2024 · 2024