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Arxiv
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GraphThought: Graph Combinatorial Optimization with Thought Generation
- Graph combinatorial optimization (GCO) problems are crucial in domains like logistics and bioinformatics.
- Large language models (LLMs) are exploring new avenues for structured reasoning in GCO but have limitations with complex tasks.
- The Optimal Thoughts Design (OTD) problem is formalized to assist in producing high-quality intermediate reasoning steps.
- GraphThought is a new framework that generates effective reasoning sequences using either forward search or backward reasoning.
- Llama-GT, an 8B-parameter model developed through fine-tuning LLMs on structured thought sequences, excels in GCO tasks.
- It outperforms larger models like DeepSeek-V3, showcasing enhanced performance without the need for increased model scale.
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