This paper describes the inference system of FZI-WIM at the SemEval-2024 Task
2: Safe Biomedical Natural Language Inference for Clinical Trials. Our system
utilizes the chain of thought (CoT) paradigm to tackle this complex reasoning
problem and further improves the CoT performance with self-consistency. Instead
of greedy decoding, we sample multiple reasoning chains with the same prompt
and make the final verification with majority voting. The self-consistent CoT
system achieves a baseline F1 score of 0.80 (1st), faithfulness score of 0.90
(3rd), and consistency score of 0.73 (12th). We release the code and data
publicly this https URL

该研究论文描述了 FZI-WIM 在 SemEval-2024 任务 2：用于临床试验的安全生物医学自然语言推理中的推理系统。我们的系统利用思维链（CoT）范式来解决这一复杂的推理问题，并通过自洽性进一步提高了 CoT 的性能。与贪婪解码不同，我们对相同提示采样多个推理链，通过多数投票进行最终验证。这个自洽的 CoT 系统取得了 0.80（第 1 名）的基线 F1 分数，0.90（第 3 名）的忠诚度分数和 0.73（第 12 名）的一致性分数。我们公开发布代码和数据，网址见链接。