Fetching the paper…
Reading the bibliography…
There is an growing interest in using Large Language Models (LLMs) in multi-agent systems to tackle interactive real-world tasks that require effective collaboration and assessing complex situations.
Scorable games: A better way to teach negotiation
L. E. Susskind · 1985
Earlier work this paper cites.
Using simulations to teach negotiation: Pedagogical theory and practice
L. E. Susskind and J. Corburn · 2000
Earlier work this paper cites.
Social iqa: Commonsense reasoning about social interactions
M. Sap, H. Rashkin, D. Chen, R. Le Bras, and Y. Choi · 2019
Earlier work this paper cites.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
A. Talmor, J. Herzig, N. Lourie, and J. Berant · 2019
Earlier work this paper cites.
Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
Earlier work this paper cites.
Language models as agent models
J. Andreas · 2022
Earlier work this paper cites.
Negotiation and honesty in artificial intelligence methods for the board game of diplomacy
J. Kramár, T. Eccles, I. Gemp, A. Tacchetti, K. R. McKee, M. Malinowski, T. Graepel, and Y. Bachrach · 2022
Earlier work this paper cites.
Neural theory-of-mind? on the limits of social intelligence in large lms
M. Sap, R. Le Bras, D. Fried, and Y. Choi · 2022
Earlier work this paper cites.
Playing repeated games with large language models
E. Akata, L. Schulz, J. Coda-Forno, S. J. Oh, M. Bethge, and E. Schulz · 2023
Earlier work this paper cites.
Gemini: a family of highly capable multimodal models
R. Anil, S. Borgeaud, Y. Wu, J.-B. Alayrac, J. Yu, R. Soricut, J. Schalkwyk, A. M. Dai, A. Hauth, et al · 2023
Earlier work this paper cites.
Improving language model negotiation with self-play and in-context learning from ai feedback
Y. Fu, H. Peng, T. Khot, and M. Lapata · 2023
Earlier work this paper cites.
Strategic reasoning with language models
K. Gandhi, D. Sadigh, and N. D. Goodman · 2023
Earlier work this paper cites.
Mistral 7b
A. Q. Jiang, A. Sablayrolles, A. Mensch, C. Bamford, D. S. Chaplot, D. d. l. Casas, F. Bressand, G. Lengyel, G. Lample, L. Saulnier, et al · 2023
Cited alongside, same era.
Task contamination: Language models may not be few-shot anymore
C. Li and J. Flanigan · 2023
Cited alongside, same era.
Camel: Communicative agents for" mind" exploration of large language model society
G. Li, H. A. A. K. Hammoud, H. Itani, D. Khizbullin, and B. Ghanem · 2023
Cited alongside, same era.
Agentbench: Evaluating llms as agents
X. Liu, H. Yu, H. Zhang, Y. Xu, X. Lei, H. Lai, Y. Gu, H. Ding, K. Men, K. Yang, et al · 2023
Cited alongside, same era.
Chameleon: Plug-and-play compositional reasoning with large language models
P. Lu, B. Peng, H. Cheng, M. Galley, K.-W. Chang, Y. N. Wu, S.-C. Zhu, and J. Gao · 2023
Cited alongside, same era.
The cofounder of google’s ai division deepmind says everybody will have their own ai-powered ’chief of staff’ over the next five years
Large language models fail on trivial alterations to theory-of-mind tasks
T. Ullman · 2023
Closest in time.
The rise and potential of large language model based agents: A survey
Z. Xi, W. Chen, X. Guo, W. He, Y. Ding, B. Hong, M. Zhang, J. Wang, S. Jin, E. Zhou, et al · 2023
Closest in time.
React: Synergizing reasoning and acting in language models
S. Yao, J. Zhao, D. Yu, I. Shafran, K. R. Narasimhan, and Y. Cao · 2023
Closest in time.
Foundational challenges in assuring alignment and safety of large language models
U. Anwar, A. Saparov, J. Rando, D. Paleka, M. Turpin, P. Hase, E. S. Lubana, E. Jenner, S. Casper, O. Sourbut, et al · 2024
Closest in time.
Evaluating language model agency through negotiations
T. R. Davidson, V. Veselovsky, M. Josifoski, M. Peyrard, A. Bosselut, M. Kosinski, and R. West · 2024
Closest in time.
Large language model capture-the-flag (LLM CTF) competition @ SaTML 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. Mok · 2023
Cited alongside, same era.
Ai deception: A survey of examples, risks, and potential solutions
P. S. Park, S. Goldstein, A. O’Gara, M. Chen, and D. Hendrycks · 2023
Cited alongside, same era.
Minding language models’(lack of) theory of mind: A plug-and-play multi-character belief tracker
M. Sclar, S. Kumar, P. West, A. Suhr, Y. Choi, and Y. Tsvetkov · 2023
Cited alongside, same era.
Role play with large language models
M. Shanahan, K. McDonell, and L. Reynolds · 2023
Cited alongside, same era.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A. Srivastava, A. Rastogi, A. Rao, A. A. M. Shoeb, A. Abid, A. Fisch, A. R. Brown, A. Santoro, A. Gupta, A. Garriga-Alonso, et al · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
H. Touvron, L. Martin, K. Stone, P. Albert, A. Almahairi, Y. Babaei, N. Bashlykov, S. Batra, P. Bhargava, S. Bhosale, et al · 2023
Cited alongside, same era.
How walmart automated supplier negotiations
HBR
Cited in the paper.
E. Debenedetti, D. Paleka, J. Rando, S. Abdelnabi, N. Carlini, M. Fritz, K. Greshake, R. Hadzic, T. Holz, D. Ippolito, Y. Zhang, L. Schönherr, and F. Tramèr · 2024
Closest in time.
Mixtral of experts
A. Q. Jiang, A. Sablayrolles, A. Roux, A. Mensch, B. Savary, C. Bamford, D. S. Chaplot, D. d. l. Casas, E. B. Hanna, F. Bressand, et al · 2024
Closest in time.
Introducing meta Llama 3: The most capable openly available LLM to date
Meta · 2024
Closest in time.
Can llms keep a secret? testing privacy implications of language models via contextual integrity theory
N. Mireshghallah, H. Kim, X. Zhou, Y. Tsvetkov, M. Sap, R. Shokri, and Y. Choi · 2024
Closest in time.
Agentic design patterns part 5: Multi-agent collaboration
A. Ng · 2024
Closest in time.
Toolformer: Language models can teach themselves to use tools
T. Schick, J. Dwivedi-Yu, R. Dessì, R. Raileanu, M. Lomeli, E. Hambro, L. Zettlemoyer, N. Cancedda, and T. Scialom · 2024
Closest in time.