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Large language models (LLMs) have revolutionized NLP research.
THE TREATMENT OF TIES IN RANKING PROBLEMS
M. G. Kendall. 1945 · 1945
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Making monolingual sentence embeddings multilingual using knowledge distillation
Nils Reimers and Iryna Gurevych. 2020 · 2020
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A statistical analysis of summarization evaluation metrics using resampling methods
Daniel Deutsch, Rotem Dror, and Dan Roth. 2021 · 2021
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SummEval: Re-evaluating summarization evaluation
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
Earlier work this paper cites.
Results of the WMT21 metrics shared task: Evaluating metrics with expert-based human evaluations on TED and news domain
Markus Freitag, Ricardo Rei, Nitika Mathur, Chi-kiu Lo, Craig Stewart, George Foster, Alon Lavie, and Ondřej Bojar. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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LangChain
Harrison Chase. 2022 · 2022
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Results of WMT22 metrics shared task: Stop using BLEU – neural metrics are better and more robust
Markus Freitag, Ricardo Rei, Nitika Mathur, Chi-kiu Lo, Craig Stewart, Eleftherios Avramidis, Tom Kocmi, George Foster, Alon Lavie, and André F. T. Martins. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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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, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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Do prompt-based models really understand the meaning of their prompts?
Albert Webson and Ellie Pavlick. 2022 · 2022
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Findings of the WMT 2022 shared task on quality estimation
Chrysoula Zerva, Frédéric Blain, Ricardo Rei, Piyawat Lertvittayakumjorn, José G. C. de Souza, Steffen Eger, Diptesh Kanojia, Duarte Alves, Constantin Orăsan, Marina Fomicheva, André F. T. Martins, and Lucia Specia. 2022 · 2022
Earlier work this paper cites.
UScore: An effective approach to fully unsupervised evaluation metrics for machine translation
Jonas Belouadi and Steffen Eger. 2023 · 2023
Earlier work this paper cites.
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 Parikh. 2023 · 2023
Cited alongside, same era.
Ties matter: Meta-evaluating modern metrics with pairwise accuracy and tie calibration
Daniel Deutsch, George Foster, and Markus Freitag. 2023 · 2023
Cited alongside, same era.
The devil is in the errors: Leveraging large language models for fine-grained machine translation evaluation
Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, Parker Riley, André Martins, Graham Neubig, Ankush Garg, Jonathan Clark, Markus Freitag, and Orhan Firat. 2023 · 2023
Cited alongside, same era.
Results of WMT23 metrics shared task: Metrics might be guilty but references are not innocent
Markus Freitag, Nitika Mathur, Chi-kiu Lo, Eleftherios Avramidis, Ricardo Rei, Brian Thompson, Tom Kocmi, Frederic Blain, Daniel Deutsch, Craig Stewart, Chrysoula Zerva, Sheila Castilho, Alon Lavie, and George Foster. 2023 · 2023
Cited alongside, same era.
Melanie Sclar, Yejin Choi, Yulia Tsvetkov, and Alane Suhr. 2023 · 2023
Later among the works it cites.
Lucas Weber, Elia Bruni, and Dieuwke Hupkes. 2023 · 2023
Later among the works it cites.
Nllg quarterly arxiv report 09/23: What are the most influential current ai papers?
Ran Zhang, Aida Kostikova, Christoph Leiter, Jonas Belouadi, Daniil Larionov, Yanran Chen, Vivian Fresen, and Steffen Eger. 2023 · 2023
Later among the works it cites.
Llama 3 model card
AI@Meta. 2024 · 2024
Closest in time.
Tower: An open multilingual large language model for translation-related tasks
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Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu. 2023 · 2023
Cited alongside, same era.
xcomet: Transparent machine translation evaluation through fine-grained error detection
Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt, Luisa Coheur, Pierre Colombo, and André F. T. Martins. 2023 · 2023
Cited alongside, same era.
Dspy: Compiling declarative language model calls into self-improving pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts. 2023 · 2023
Cited alongside, same era.
Which is better? exploring prompting strategy for LLM-based metrics
JoongHoon Kim, Sangmin Lee, Seung Hun Han, Saeran Park, Jiyoon Lee, Kiyoon Jeong, and Pilsung Kang. 2023 · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
Cited alongside, same era.
The language of prompting: What linguistic properties make a prompt successful?
Alina Leidinger, Robert van Rooij, and Ekaterina Shutova. 2023 · 2023
Cited alongside, same era.
The eval4nlp 2023 shared task on prompting large language models as explainable metrics
Christoph Leiter, Juri Opitz, Daniel Deutsch, Yang Gao, Rotem Dror, and Steffen Eger. 2023 · 2023
Cited alongside, same era.
Large language models understand and can be enhanced by emotional stimuli
Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, and Xing Xie. 2023 · 2023
Cited alongside, same era.
Duarte M. Alves, José Pombal, Nuno M. Guerreiro, Pedro H. Martins, João Alves, Amin Farajian, Ben Peters, Ricardo Rei, Patrick Fernandes, Sweta Agrawal, Pierre Colombo, José G. C. de Souza, and André F. T. Martins. 2024 · 2024
Closest in time.
Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
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Towards explainable evaluation metrics for machine translation
Christoph Leiter, Piyawat Lertvittayakumjorn, Marina Fomicheva, Wei Zhao, Yang Gao, and Steffen Eger. 2024 · 2024
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Leveraging large language models for nlg evaluation: A survey
Zhen Li, Xiaohan Xu, Tao Shen, Can Xu, Jia-Chen Gu, and Chongyang Tao. 2024 · 2024
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Error analysis prompting enables human-like translation evaluation in large language models
Qingyu Lu, Baopu Qiu, Liang Ding, Kanjian Zhang, Tom Kocmi, and Dacheng Tao. 2024 · 2024
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State of what art? a call for multi-prompt llm evaluation
Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, and Gabriel Stanovsky. 2024 · 2024
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Introducing chatgpt
OpenAI. 2023 · 2024
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Mind your format: Towards consistent evaluation of in-context learning improvements
Anton Voronov, Lena Wolf, and Max Ryabinin. 2024 · 2024
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