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Language models are few-shot learners
Original
Tom B Brown · 2020
Earlier work this paper cites.
FOLIO: Natural language reasoning with first-order logic
Original
Simeng Han, Hailey Schoelkopf, Yilun Zhao, Zhenting Qi, Martin Riddell, Luke Benson, Lucy Sun, Ekaterina Zubova, Yujie Qiao, Matthew Burtell, et al · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Earlier work this paper cites.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Original
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 2022
Earlier work this paper cites.
Challenging BIG-bench tasks and whether chain-of-thought can solve them
Original
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V Le, Ed H Chi, Denny Zhou, et al · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
Improving factuality and reasoning in language models through multiagent debate
Original
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch · 2023
Earlier work this paper cites.
Gemini: A family of highly capable multimodal models
Original
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
Earlier work this paper cites.

Similar

Large language models cannot self-correct reasoning yet
Original
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
Cited alongside, same era.
Encouraging divergent thinking in large language models through multi-agent debate
Original
Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Zhaopeng Tu, and Shuming Shi · 2023
Cited alongside, same era.
ART: Automatic multi-step reasoning and tool-use for large language models
Original
Bhargavi Paranjape, Scott Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, and Marco Tulio Ribeiro · 2023
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Original
X Wang, J Wei, D Schuurmans, Q Le, E Chi, S Narang, A Chowdhery, and D Zhou · 2023
Cited alongside, same era.

Then

Larimar: Large language models with episodic memory control
Original
Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie Lozano, Georgios Kollias, Vijil Chenthamarakshan, Soham Dan, et al · 2024
Later among the works it cites.
Don’t hallucinate, abstain: Identifying LLM knowledge gaps via multi-LLM collaboration
Original
Shangbin Feng, Weijia Shi, Yike Wang, Wenxuan Ding, Vidhisha Balachandran, and Yulia Tsvetkov · 2024
Later among the works it cites.
Debating with more persuasive LLMs leads to more truthful answers
Original
Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R Bowman, Tim Rocktäschel, and Ethan Perez · 2024
Later among the works it cites.
Gecko: Versatile text embeddings distilled from large language models
Original
Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, et al · 2024
Later among the works it cites.

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2025

Enhancing Reasoning with Collaboration and Memory

Michelman, Julie, Baratalipour, Nasrin, Abueg, Matthew

Understand

We envision a continuous collaborative learning system where groups of LLM agents work together to solve reasoning problems, drawing on memory they collectively build to improve performance as they gain experience.

This work establishes the foundations for such a system by studying the interoperability of chain-of-thought reasoning styles, multi-agent collaboration, and memory banks.
Extending beyond the identical agents of self-consistency, we introduce varied-context agents with diverse exemplars and a summarizer agent in place of voting.
We generate frozen and continuously learned memory banks of exemplars and pair them with fixed, random, and similarity-based retrieval mechanisms.

Built on

Language models are few-shot learners
Original
Tom B Brown · 2020
Earlier work this paper cites.
FOLIO: Natural language reasoning with first-order logic
Original
Simeng Han, Hailey Schoelkopf, Yilun Zhao, Zhenting Qi, Martin Riddell, Luke Benson, Lucy Sun, Ekaterina Zubova, Yujie Qiao, Matthew Burtell, et al · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
Earlier work this paper cites.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Original
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 2022
Earlier work this paper cites.
Challenging BIG-bench tasks and whether chain-of-thought can solve them
Original
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V Le, Ed H Chi, Denny Zhou, et al · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
Improving factuality and reasoning in language models through multiagent debate
Original
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch · 2023
Earlier work this paper cites.
Gemini: A family of highly capable multimodal models
Original
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
Earlier work this paper cites.

Similar

Large language models cannot self-correct reasoning yet
Original
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
Cited alongside, same era.
Encouraging divergent thinking in large language models through multi-agent debate
Original
Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Zhaopeng Tu, and Shuming Shi · 2023
Cited alongside, same era.
ART: Automatic multi-step reasoning and tool-use for large language models
Original
Bhargavi Paranjape, Scott Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, and Marco Tulio Ribeiro · 2023
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Original
X Wang, J Wei, D Schuurmans, Q Le, E Chi, S Narang, A Chowdhery, and D Zhou · 2023
Cited alongside, same era.

Then

Larimar: Large language models with episodic memory control
Original
Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarath Swaminathan, Sihui Dai, Aurélie Lozano, Georgios Kollias, Vijil Chenthamarakshan, Soham Dan, et al · 2024
Later among the works it cites.
Don’t hallucinate, abstain: Identifying LLM knowledge gaps via multi-LLM collaboration
Original
Shangbin Feng, Weijia Shi, Yike Wang, Wenxuan Ding, Vidhisha Balachandran, and Yulia Tsvetkov · 2024
Later among the works it cites.
Debating with more persuasive LLMs leads to more truthful answers
Original
Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R Bowman, Tim Rocktäschel, and Ethan Perez · 2024
Later among the works it cites.
Gecko: Versatile text embeddings distilled from large language models
Original
Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, et al · 2024
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Large language models as analogical reasoners

Original

Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H Chi, and Denny Zhou · 2023

Cited alongside, same era.

Many-shot in-context learning

Original

Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, et al · 2024

Cited alongside, same era.

How well can LLMs negotiate? NegotiationArena platform and analysis

Original

Federico Bianchi, Patrick John Chia, Mert Yuksekgonul, Jacopo Tagliabue, Dan Jurafsky, and James Zou · 2024

Cited alongside, same era.

Reconcile: Round-table conference improves reasoning via consensus among diverse LLMs

Original

Justin Chih-Yao Chen, Swarnadeep Saha, and Mohit Bansal

Cited in the paper.

Universal Self-Consistency for large language model generation

Original

Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, and Denny Zhou