Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search

Large language models are learnable planners for long-term recommendation

Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, and Fuli Feng. 2024a · 1903

Earlier work this paper cites.

The influence curve and its role in robust estimation

Frank R Hampel. 1974 · 1974

Earlier work this paper cites.

Graph Theory with Applications

J. A. Bondy and U. S. R. Murty. 1976 · 1976

Earlier work this paper cites.

Graph Theory and Its Applications

Jonathan L. Gross and Jay Yellen. 2005 · 2005

Earlier work this paper cites.

The goldilocks principle: Reading children’s books with explicit memory representations

Felix Hill, Antoine Bordes, Sumit Chopra, and Jason Weston. 2016 · 2016

Earlier work this paper cites.

Mastering the game of go with deep neural networks and tree search

David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis. 2016 · 2016

Earlier work this paper cites.

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

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

Earlier work this paper cites.

Understanding black-box predictions via influence functions

Pang Wei Koh and Percy Liang. 2017 · 2017

Earlier work this paper cites.

Hotpotqa: A dataset for diverse, explainable multi-hop question answering

Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018

Earlier work this paper cites.

Constructing A multi-hop QA dataset for comprehensive evaluation of reasoning steps

Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa. 2020 · 2020

Earlier work this paper cites.

Estimating training data influence by tracing gradient descent

Garima Pruthi, Frederick Liu, Satyen Kale, and Mukund Sundararajan. 2020 · 2020

Earlier work this paper cites.

Think you have solved direct-answer question answering? try arc-da, the direct-answer AI2 reasoning challenge

Original

Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, and Peter Clark. 2021 · 2021

Earlier work this paper cites.

Measuring massive multitask language understanding

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

Earlier work this paper cites.

Lora: Low-rank adaptation of large language models

Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022

Earlier work this paper cites.

Chain-of-thought prompting elicits reasoning in large language models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022

Earlier work this paper cites.

Fireact: Toward language agent fine-tuning

Original

Baian Chen, Chang Shu, Ehsan Shareghi, Nigel Collier, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023

Earlier work this paper cites.

Reasoning with language model is planning with world model

Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, and Zhiting Hu. 2023 · 2023

Earlier work this paper cites.

Dspy: Compiling declarative language model calls into self-improving pipelines

Original

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.

CAMEL: communicative agents for "mind" exploration of large language model society

Guohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. 2023 · 2023

Cited alongside, same era.

GPT-4 technical report

Original

OpenAI. 2023 · 2023

Cited alongside, same era.

TRAK: attributing model behavior at scale

Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, and Aleksander Madry. 2023 · 2023

Cited alongside, same era.

Direct preference optimization: Your language model is secretly a reward model

Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, and Chelsea Finn. 2023 · 2023

MALT: improving reasoning with multi-agent LLM training

Original

Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Markian Rybchuk, Philip H. S. Torr, Ivan Laptev, Fabio Pizzati, Ronald Clark, and Christian Schröder de Witt. 2024 · 2024

Later among the works it cites.

Optimizing instructions and demonstrations for multi-stage language model programs

Krista Opsahl-Ong, Michael J. Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, and Omar Khattab. 2024 · 2024

Later among the works it cites.

Iterative reasoning preference optimization

Original

Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, and Jason Weston. 2024 · 2024

Later among the works it cites.

Mutual reasoning makes smaller llms stronger problem-solvers

Original

Zhenting Qi, Mingyuan Ma, Jiahang Xu, Li Lyna Zhang, Fan Yang, and Mao Yang. 2024 · 2024

Later among the works it cites.