PokerBench: Training Large Language Models to become Professional Poker Players

Language models are few-shot learners

Brown, T.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J. D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 1901

Earlier work this paper cites.

Games with incomplete information

Harsanyi, J. C. 1995 · 1995

Earlier work this paper cites.

Deep blue

Campbell, M.; Hoane Jr, A. J.; and Hsu, F.-h. 2002 · 2002

Earlier work this paper cites.

Measuring massive multitask language understanding

Original

Hendrycks, D.; Burns, C.; Basart, S.; Zou, A.; Mazeika, M.; Song, D.; and Steinhardt, J. 2020 · 2009

Earlier work this paper cites.

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

Silver, D.; Huang, A.; Maddison, C. J.; Guez, A.; Sifre, L.; Van Den Driessche, G.; Schrittwieser, J.; Antonoglou, I.; Panneershelvam, V.; Lanctot, M.; et al. 2016 · 2016

Earlier work this paper cites.

Superhuman AI for heads-up no-limit poker: Libratus beats top professionals

Brown, N.; and Sandholm, T. 2018 · 2018

Earlier work this paper cites.

Commonsenseqa: A question answering challenge targeting commonsense knowledge

Original

Talmor, A.; Herzig, J.; Lourie, N.; and Berant, J. 2018 · 2018

Earlier work this paper cites.

GLUE: A multi-task benchmark and analysis platform for natural language understanding

Original

Wang, A.; Singh, A.; Michael, J.; Hill, F.; Levy, O.; and Bowman, S. R. 2018 · 2018

Earlier work this paper cites.

Deep counterfactual regret minimization

Brown, N.; Lerer, A.; Gross, S.; and Sandholm, T. 2019 · 2019

Earlier work this paper cites.

Superhuman AI for multiplayer poker

Brown, N.; and Sandholm, T. 2019 · 2019

Cited alongside, same era.

Language models are unsupervised multitask learners

Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; Sutskever, I.; et al. 2019 · 2019

Cited alongside, same era.

Superglue: A stickier benchmark for general-purpose language understanding systems

Wang, A.; Pruksachatkun, Y.; Nangia, N.; Singh, A.; Michael, J.; Hill, F.; Levy, O.; and Bowman, S. 2019 · 2019

Cited alongside, same era.

Training verifiers to solve math word problems

Original

Cobbe, K.; Kosaraju, V.; Bavarian, M.; Chen, M.; Jun, H.; Kaiser, L.; Plappert, M.; Tworek, J.; Hilton, J.; Nakano, R.; et al. 2021 · 2021

Cited alongside, same era.

ChatGPT - https://openai.com/blog/chatgpt#OpenAI

OpenAI. 2022 · 2022

Cited alongside, same era.

Training language models to follow instructions with human feedback

GPT-4 Technical Report - https://cdn.openai.com/papers/gpt-4.pdf

OpenAI. 2023 · 2023

Later among the works it cites.

Llama 2: Open foundation and fine-tuned chat models, 2023

Original

Touvron, H.; Martin, L.; Stone, K.; Albert, P.; Almahairi, A.; Babaei, Y.; Bashlykov, N.; Batra, S.; Bhargava, P.; Bhosale, S.; et al. 2023 · 2023

Later among the works it cites.

A survey on large language model-based game agents

Original

Hu, S.; Huang, T.; Ilhan, F.; Tekin, S.; Liu, G.; Kompella, R.; and Liu, L. 2024 · 2024

Later among the works it cites.

PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold’em via Large Language Model

Original

Huang, C.; Cao, Y.; Wen, Y.; Zhou, T.; and Zhang, Y. 2024 · 2024

Later among the works it cites.

Llama 3 - https://ai.meta.com/blog/meta-llama-3/

Meta. 2024 · 2024