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As the applicability of Large Language Models (LLMs) extends beyond traditional text processing tasks, there is a burgeoning interest in their potential to excel in planning and reasoning assignments, realms traditionally reserved for System 2 cognitive competencies.
Thinking, fast and slow
Kahneman, D · 2011
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Gpt-3.5: Language model, 2022
OpenAI · 2022
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Large language models still can’t plan (a benchmark for llms on planning and reasoning about change)
Valmeekam, K., Olmo, A., Sreedharan, S., and Kambhampati, S · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., Zhou, D., et al · 2022
Earlier work this paper cites.
Tool documentation enables zero-shot tool-usage with large language models
Hsieh, C.-Y., Chen, S.-A., Li, C.-L., Fujii, Y., Ratner, A., Lee, C.-Y., Krishna, R., and Pfister, T · 2023
Earlier work this paper cites.
Gpt-4: Language model, 2023
OpenAI · 2023
Earlier work this paper cites.
Art: Automatic multi-step reasoning and tool-use for large language models
Paranjape, B., Lundberg, S., Singh, S., Hajishirzi, H., Zettlemoyer, L., and Ribeiro, M. T · 2023
Earlier work this paper cites.
The rise and potential of large language model based agents: A survey
Xi, Z., Chen, W., Guo, X., He, W., Ding, Y., Hong, B., Zhang, M., Wang, J., Jin, S., Zhou, E., et al · 2023
Cited alongside, same era.
A survey on evaluation of large language models
Chang, Y., Wang, X., Wang, J., Wu, Y., Yang, L., Zhu, K., Chen, H., Yi, X., Wang, C., Wang, Y., et al · 2024
Cited alongside, same era.
”task success” is not enough: Investigating the use of video-language models as behavior critics for catching undesirable agent behaviors, 2024
Guan, L., Zhou, Y., Liu, D., Zha, Y., Amor, H. B., and Kambhampati, S · 2024
Cited alongside, same era.
Can large language models reason and plan?
Kambhampati, S · 2024
Cited alongside, same era.
Llms can’t plan, but can help planning in llm-modulo frameworks, 2024
Kambhampati, S., Valmeekam, K., Guan, L., Stechly, K., Verma, M., Bhambri, S., Saldyt, L., and Murthy, A · 2024
Cited alongside, same era.
Reflexion: Language agents with verbal reinforcement learning
Shinn, N., Cassano, F., Gopinath, A., Narasimhan, K., and Yao, S · 2024
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Theory of mind abilities of large language models in human-robot interaction: An illusion?
Verma, M., Bhambri, S., and Kambhampati, S · 2024
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Theory of mind abilities of large language models in human-robot interaction: An illusion?
Verma, M., Bhambri, S., and Kambhampati, S · 2024
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A survey on large language model based autonomous agents
Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., Lin, Y., et al · 2024
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Travelplanner: A benchmark for real-world planning with language agents
Xie, J., Zhang, K., Chen, J., Zhu, T., Lou, R., Tian, Y., Xiao, Y., and Su, Y · 2024
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Toolformer: Language models can teach themselves to use tools
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Hambro, E., Zettlemoyer, L., Cancedda, N., and Scialom, T · 2024
Cited alongside, same era.
Chain of thoughtlessness: An analysis of cot in planning, 2024a
Stechly, K., Valmeekam, K., and Kambhampati, S
Cited in the paper.
On the self-verification limitations of large language models on reasoning and planning tasks, 2024b
Stechly, K., Valmeekam, K., and Kambhampati, S
Cited in the paper.
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., and Cao, Y · 2024
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