HJYao00/Mulberry

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1243 stars · 113 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Mulberry is a research implementation of an o1-like multimodal large language model (MLLM) that performs step-by-step reasoning and reflection via collective Monte Carlo Tree Search (MCTS). It includes released model checkpoints (LLaVA/Llama and Qwen2-VL based), reasoning inference code, and evaluation code accompanying a NeurIPS 2025 spotlight paper.

Use cases

• run o1-style reasoning with a multimodal LLM
• generate reasoning and reflection traces with MCTS
• evaluate a reasoning MLLM on multimodal benchmarks
• fine-tune a multimodal model on reasoning SFT data
• reproduce a NeurIPS 2025 MLLM reasoning paper

When to choose

• you need o1-like chain-of-thought reasoning for image+text inputs
• you want to experiment with MCTS-based reasoning data generation
• you want ready checkpoints and evaluation code for reasoning MLLMs

When to avoid

• you need a production-ready inference server with support guarantees
• you need a permissively licensed project (no license is specified)
• you only need text-only reasoning without multimodal inputs

Facets

library · maturity active

machine-learning deep-learning llm-inference llm-training agent-framework large-language-models machine-learning computer-vision artificial-intelligence python multimodal mcts reasoning reflection mllm chain-of-thought research-code neurips research gpu linux

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