Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs

Felix Fricke, Simon Malberg, Georg Groh


Abstract
Prompting schemes such as Chain of Thought, Tree of Thoughts, and Graph of Thoughts can significantly enhance the reasoning capabilities of large language models. However, most existing schemes require users to define static, problem-specific reasoning structures that lack adaptability to dynamic or unseen problem types. Additionally, these schemes are often under-optimized in terms of hyperparameters, prompts, runtime, and prompting cost. To address these limitations, we introduce Framework of Thoughts (FoT) – a general-purpose foundation framework for implementing and optimizing dynamic reasoning schemes. FoT comes with built-in features for hyperparameter tuning, prompt optimization, parallel execution, and intelligent caching, unlocking the latent performance potential of reasoning schemes. We demonstrate FoT’s capabilities by implementing three popular schemes – Tree of Thoughts, Graph of Thoughts, and ProbTree – within FoT. We empirically show that FoT enables significantly faster execution, reduces costs, and achieves better task scores through optimization. We release our codebase to facilitate the development of future dynamic and efficient reasoning schemes.
Anthology ID:
2026.surgellm-1.8
Volume:
Proceedings of the First Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era (SURGeLLM 2026)
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Vivek Gupta, Kaize Ding, Harsha Kokel, Yue Zhao, Amit Agarwal, Yu Wang, Michael Glass, Yu Zhang, Kavitha Srinivas, Xiusi Chen, Oktie Hassanzadeh, Qi Zhu, Shuaichen Chang, Yuan Luo
Venues:
SURGeLLM | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
132–151
Language:
URL:
https://aclanthology.org/2026.surgellm-1.8/
DOI:
Bibkey:
Cite (ACL):
Felix Fricke, Simon Malberg, and Georg Groh. 2026. Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs. In Proceedings of the First Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era (SURGeLLM 2026), pages 132–151, San Diego, California, United States. Association for Computational Linguistics.
Cite (Informal):
Framework of Thoughts: A Foundation Framework for Dynamic and Optimized Reasoning based on Chains, Trees, and Graphs (Fricke et al., SURGeLLM 2026)
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PDF:
https://aclanthology.org/2026.surgellm-1.8.pdf