Papers with Llama-Base model

1 papers
How Do Humans Write Code? Large Models Do It the Same Way Too (2024.emnlp-main)

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Challenge: Program-of-Thought (PoT) replaces natural language-based Chain-ofThough (CoT) but introduces more reasoning errors, such as incorrect formulas or flawed logic, compared to CoT.
Approach: They propose a method that integrates CoT and Program-of-Thought to achieve more accurate reasoning and reinforcement learning.
Outcome: The proposed method achieves an average improvement of 6.5% on the Llama-Base model and 4.3% on the Mistral-Bass model across 8 mathematical calculation datasets.

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