Cool-Fusion: Fuse Large Language Models without Training

TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension

Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017

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DROP: A reading comprehension benchmark requiring discrete reasoning over paragraphs

Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. 2019 · 2019

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CoQA: A conversational question answering challenge

Siva Reddy, Danqi Chen, and Christopher D. Manning. 2019 · 2019

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Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021

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Measuring mathematical problem solving with the math dataset

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

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SummaReranker: A multi-task mixture-of-experts re-ranking framework for abstractive summarization

Mathieu Ravaut, Shafiq Joty, and Nancy Chen. 2022 · 2022

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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Mitchell Wortsman, Gabriel Ilharco, Samir Ya Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt. 2022 · 2022

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Specializing smaller language models towards multi-step reasoning

Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, and Tushar Khot. 2023 · 2023

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A framework for few-shot language model evaluation

Leo Gao, Jonathan Tow, Baber Abbasi, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Alain Le Noac’h, Haonan Li, Kyle McDonell, Niklas Muennighoff, Chris Ociepa, Jason Phang, Laria Reynolds, Hailey Schoelkopf, Aviya Skowron, Lintang Sutawika, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou. 2023 · 2023

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LLM-blender: Ensembling large language models with pairwise ranking and generative fusion

Dongfu Jiang, Xiang Ren, and Bill Yuchen Lin. 2023 · 2023

Cited alongside, same era.

Language models are greedy reasoners: A systematic formal analysis of chain-of-thought

Abulhair Saparov and He He. 2023 · 2023

Cited alongside, same era.

Sub-character tokenization for Chinese pretrained language models

Chenglei Si, Zhengyan Zhang, Yingfa Chen, Fanchao Qi, Xiaozhi Wang, Zhiyuan Liu, Yasheng Wang, Qun Liu, and Maosong Sun. 2023 · 2023

Cited alongside, same era.

GLM-130B: an open bilingual pre-trained model

Original

Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, et al. 2023 · 2023

Later among the works it cites.

LLM augmented LLMs: Expanding capabilities through composition

Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, and Partha Talukdar. 2024 · 2024

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Phi-3 technical report: A highly capable language model locally on your phone

Original

Marah Abdin et al. 2024 · 2024

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MetaGPT: Meta programming for a multi-agent collaborative framework

Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, and Jürgen Schmidhuber. 2024 · 2024

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Population parameter averaging (PAPA)

Alexia Jolicoeur-Martineau, Emy Gervais, Kilian FATRAS, Yan Zhang, and Simon Lacoste-Julien. 2024 · 2024