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The surge of LLM studies makes synthesizing their findings challenging.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2005
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Interrater reliability: the kappa statistic
Mary L McHugh. 2012 · 2012
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A structured review of the validity of bleu
Ehud Reiter. 2018 · 2018
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The use of rating and likert scales in natural language generation human evaluation tasks: A review and some recommendations
Jacopo Amidei, Paul Piwek, and Alistair Willis. 2019 · 2019
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Using machine learning and natural language processing to review and classify the medical literature on cancer susceptibility genes
Yujia Bao, Zhengyi Deng, Yan Wang, Heeyoon Kim, Victor Diego Armengol, Francisco Acevedo, Nofal Ouardaoui, Cathy Wang, Giovanni Parmigiani, Regina Barzilay, et al. 2019 · 2019
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Identification of tasks, datasets, evaluation metrics, and numeric scores for scientific leaderboards construction
Yufang Hou, Charles Jochim, Martin Gleize, Francesca Bonin, and Debasis Ganguly. 2019 · 2019
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Automated early leaderboard generation from comparative tables
Mayank Singh, Rajdeep Sarkar, Atharva Vyas, Pawan Goyal, Animesh Mukherjee, and Soumen Chakrabarti. 2019 · 2019
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Axcell: Automatic extraction of results from machine learning papers
Marcin Kardas, Piotr Czapla, Pontus Stenetorp, Sebastian Ruder, Sebastian Riedel, Ross Taylor, and Robert Stojnic. 2020 · 2020
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Artificial intelligence: A powerful paradigm for scientific research
Yongjun Xu, Xin Liu, Xin Cao, Changping Huang, Enke Liu, Sen Qian, Xingchen Liu, Yanjun Wu, Fengliang Dong, Cheng-Wei Qiu, et al. 2021 · 2021
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al. 2022 · 2022
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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. 2022 · 2022
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Can language models learn from explanations in context?
Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, Kory Mathewson, Mh Tessler, Antonia Creswell, James McClelland, Jane Wang, and Felix Hill. 2022 · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022
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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
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Telin: Table entity linker for extracting leaderboards from machine learning publications
Sean Yang, Chris Tensmeyer, and Curtis Wigington. 2022 · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Earlier work this paper cites.
Schema-driven information extraction from heterogeneous tables
Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, and Alan Ritter. 2023 · 2023
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Batch prompting: Efficient inference with large language model apis
Zhoujun Cheng, Jungo Kasai, and Tao Yu. 2023 · 2023
Earlier work this paper cites.
A taxonomy and review of generalization research in nlp
Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, et al. 2023 · 2023
Cited alongside, same era.
Prometheus: Inducing fine-grained evaluation capability in language models
Seungone Kim, Jamin Shin, Yejin Cho, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, et al. 2023 · 2023
Cited alongside, same era.
G-eval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023a · 2023
Cited alongside, same era.
G-eval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023b · 2023
Cited alongside, same era.
A call for standardization and validation of text style transfer evaluation
Phil Ostheimer, Mayank Nagda, Marius Kloft, and Sophie Fellenz. 2023 · 2023
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al. 2024 · 2024
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Orkg-leaderboards: a systematic workflow for mining leaderboards as a knowledge graph
Salomon Kabongo, Jennifer D’Souza, and Sören Auer. 2024 · 2024
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T \ \backslash " ulu 3: Pushing frontiers in open language model post-training
Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison, Faeze Brahman, Lester James V Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, et al. 2024 · 2024
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Ryan Liu, Jiayi Geng, Addison J Wu, Ilia Sucholutsky, Tania Lombrozo, and Thomas L Griffiths. 2024 · 2024
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On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning
Omar Shaikh, Hongxin Zhang, William Held, Michael Bernstein, and Diyi Yang. 2023 · 2023
Cited alongside, same era.
Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, Katie Millican, et al. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Towards understanding chain-of-thought prompting: An empirical study of what matters
Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, and Huan Sun. 2023 · 2023
Cited alongside, same era.
Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning
Lucas Weber, Elia Bruni, and Dieuwke Hupkes. 2023 · 2023
Cited alongside, same era.
Larger language models do in-context learning differently
Jerry Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, et al. 2023 · 2023
Cited alongside, same era.
Appraising the potential uses and harms of llms for medical systematic reviews
Hye Sun Yun, Iain J Marshall, Thomas A Trikalinos, and Byron C Wallace. 2023 · 2023
Cited alongside, same era.
Chuanhao Lv, Kaiyan Chang, Ziyang Wang, Shuhan Zhou, Nuo Xu, et al. 2024 · 2024
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Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller. 2024 · 2024
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Discoverybench: Towards data-driven discovery with large language models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Bhavana Dalvi Mishra, Abhijeetsingh Meena, Aryan Prakhar, Tirth Vora, Tushar Khot, Ashish Sabharwal, and Peter Clark. 2024 · 2024
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Openai o1-preview
OpenAI. 2024 · 2024
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Abigsurveyofllms
Junhao Ruan, Long Meng, Weiqiao Shan, Tong Xiao, and Jingbo Zhu. 2024 · 2024
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Efficient performance tracking: Leveraging large language models for automated construction of scientific leaderboards
Furkan Şahinuç, Thy Thy Tran, Yulia Grishina, Yufang Hou, Bei Chen, and Iryna Gurevych. 2024 · 2024
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Prompting llms to compose meta-review drafts from peer-review narratives of scholarly manuscripts
Shubhra Kanti Karmaker Santu, Sanjeev Kumar Sinha, Naman Bansal, Alex Knipper, Souvika Sarkar, John Salvador, Yash Mahajan, Sri Guttikonda, Mousumi Akter, Matthew Freestone, et al. 2024 · 2024
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Legobench: Leaderboard generation benchmark for scientific models
Shruti Singh, Shoaib Alam, and Mayank Singh. 2024 · 2024
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To cot or not to cot? chain-of-thought helps mainly on math and symbolic reasoning
Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, Dongwei Jiang, Manya Wadhwa, Prasann Singhal, Xinyu Zhao, Xi Ye, Kyle Mahowald, and Greg Durrett. 2024 · 2024
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Language models don’t always say what they think: unfaithful explanations in chain-of-thought prompting
Miles Turpin, Julian Michael, Ethan Perez, and Samuel Bowman. 2024 · 2024
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Charxiv: Charting gaps in realistic chart understanding in multimodal llms
Zirui Wang, Mengzhou Xia, Luxi He, Howard Chen, Yitao Liu, Richard Zhu, Kaiqu Liang, Xindi Wu, Haotian Liu, Sadhika Malladi, et al. 2024 · 2024
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2024 · 2024
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Hye Sun Yun, David Pogrebitskiy, Iain J Marshall, and Byron C Wallace. 2024 · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al. 2025 · 2025
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Are nlp models really able to solve simple math word problems?
Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2094
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