Advancing LLM Reasoning Generalists with Preference Trees
FreeAbout Advancing LLM Reasoning Generalists with Preference Trees
Eurus is a suite of large language models (LLMs) optimized for reasoning, fine-tuned from Mistral-7B and CodeLlama-70B. It achieves state-of-the-art results among open-source models on benchmarks covering mathematics, code generation, and logical reasoning. Notably, Eurus-70B surpasses GPT-3.5 Turbo in comprehensive reasoning tests, with a 33.3% pass@1 accuracy on LeetCode and 32.6% on TheoremQA, outperforming existing open-source models by over 13.3%. Its strong performance is attributed to UltraInteract, a newly curated large-scale, high-quality alignment dataset designed for complex reasoning tasks, which includes preference trees with diverse reasoning chains, multi-turn interaction trajectories, and pairwise data for preference learning.
Key Features
Pros & Cons
- Achieves state-of-the-art reasoning performance among open-source models
- Surpasses GPT-3.5 Turbo on a comprehensive reasoning benchmark suite
- Large margins of improvement on challenging benchmarks like LeetCode and TheoremQA
- Open-source models and data are publicly available
- UltraInteract dataset enables effective preference learning for reasoning
- Primarily evaluated on reasoning benchmarks; general conversational ability and other NLP tasks not assessed
- May require significant computational resources for inference due to model size (70B parameters)
- Dependence on base models (Mistral-7B, CodeLlama-70B) which have their own limitations