ChatGPT 的回答能否提升传统自然语言处理？
Can ChatGPT's Responses Boost Traditional Natural Language Processing?
AI总结：
本文研究 ChatGPT 的详细回答与现有 NLP 方法融合能否提升情感计算性能，在情感分析、自杀倾向检测和大五人格评估三个任务上验证了其新颖知识可通过早期或晚期融合改进传统模型。
摘要：
基础模型的应用正在稳步扩展，尤其是随着 ChatGPT 的推出以及其他基础模型的发布。这些模型展示了在没有经过专门训练的情况下解决各类问题的新兴能力潜力。此前的一项工作已在情感计算任务中证明了这些新兴能力；其性能质量与传统自然语言处理（NLP）技术相近，但仍不及专门训练的模型，例如对 RoBERTa 语言模型进行微调。在本工作中，我们进一步探索 ChatGPT 是否拥有新颖知识，能够在与现有专门模型融合时增强这些模型。我们通过研究 ChatGPT 针对下游任务给出的详细回答的效用，以及研究将其与现有 NLP 方法融合的效用来实现这一目标。该研究在三个情感计算问题上进行，即情感分析、自杀倾向检测和大五人格评估。结果表明，ChatGPT 确实拥有新颖知识，可以通过融合（无论是早期融合还是晚期融合）来改进现有的 NLP 技术。
英文摘要：
The employment of foundation models is steadily expanding, especially with the launch of ChatGPT and the release of other foundation models. These models have shown the potential of emerging capabilities to solve problems, without being particularly trained to solve. A previous work demonstrated these emerging capabilities in affective computing tasks; the performance quality was similar to traditional Natural Language Processing (NLP) techniques, but falling short of specialised trained models, like fine-tuning of the RoBERTa language model. In this work, we extend this by exploring if ChatGPT has novel knowledge that would enhance existing specialised models when they are fused together. We achieve this by investigating the utility of verbose responses from ChatGPT about solving a downstream task, in addition to studying the utility of fusing that with existing NLP methods. The study is conducted on three affective computing problems, namely sentiment analysis, suicide tendency detection, and big-five personality assessment. The results conclude that ChatGPT has indeed novel knowledge that can improve existing NLP techniques by way of fusion, be it early or late fusion.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
