LiTS: A Modular Framework for LLM Tree Search
LiTS is a modular Python framework for LLM reasoning via tree search. It decomposes tree search into three reusable components (Policy, Transition, and RewardModel) that plug into algorithms like MCTS and BFS. A decorator-based registry enables domain experts to extend to new domains by registering components, and algorithmic researchers to implement custom search algorithms. We demonstrate composability on MATH500 (language reasoning), Crosswords (environment planning), and MapEval (tool use), showing that components and algorithms are orthogonal: components are reusable across algorithms within each task type, and algorithms work across all components and domains. We also report a mode-...
| Authors | Xinzhe Li, Yaguang Tao |
|---|---|
| Primary category | cs.AI |
| Published | 28 February 2026 |
| Last updated at source | 17 May 2026 |
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