ZonglinY/MOOSE-Star-HC-R1D-7B
ZonglinY/MOOSE-Star-HC-R1D-7B is a 7 billion parameter language model, fine-tuned from DeepSeek-R1-Distill-Qwen-7B, specifically designed for generating scientific hypotheses. It excels at composing incremental "delta hypotheses" by integrating new research paper inspirations with existing research questions and background surveys. This model focuses on breaking down hypothesis generation into key components: inspiration, motivation, mechanism, and methodology, making it ideal for structured scientific discovery workflows.
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MOOSE-Star-HC-R1D-7B: Scientific Hypothesis Generation
MOOSE-Star-HC-R1D-7B is a 7 billion parameter model, based on DeepSeek-R1-Distill-Qwen-7B, specialized in generating scientific hypotheses. Developed by Zonglin Yang and Lidong Bing, this model is fine-tuned for incremental hypothesis composition, a critical task in scientific discovery. It operates by taking a research question, background survey, and a new inspiration paper (title + abstract) to output a "delta hypothesis."
Key Capabilities
- Structured Hypothesis Generation: Deconstructs hypotheses into four components: Inspiration, Motivation (WHY), Mechanism (HOW IT WORKS), and Methodology (HOW IT'S INTEGRATED).
- Incremental Composition: Designed to integrate new research insights with existing knowledge to refine or expand hypotheses.
- Scientific Discovery Workflow: Optimized for use in workflows where hypotheses are built up iteratively.
- Performance: Outperforms its base model, DeepSeek-R1-Distill-Qwen-7B, in rubric-based evaluations for hypothesis composition, achieving a total score of 4.74 compared to the base model's 4.05.
Training Details
The model was trained using full-parameter SFT (ZeRO-3) on 114,548 samples from the TOMATO-Star-SFT-Data-R1D-32B HC split, with a cutoff length of 8192 tokens. It utilizes a deepseekr1 chat template.
Usage
Users can integrate this model by cloning the MOOSE-Star repository to access necessary prompt templates and utilities. The model is designed to be used with a specific prompt format that guides the generation of structured delta hypotheses.