论文标题
问我需要什么：使用GPT-3的知识进行产品检索
Ask Me What You Need: Product Retrieval using Knowledge from GPT-3
论文作者
论文摘要
随着在线商品变得越来越普遍，许多研究着重于基于嵌入的方法，在语义空间中可以查询和产品。这些方法减轻了查询和产品语言之间词汇不匹配的问题。但是，过去的研究通常涉及精确描述该产品的查询，并且仍然需要回答可能需要常识知识的不精确查询，即“我应该让妈妈在母亲节中得到什么。”在本文中，我们提出了一个基于GPT-3的产品检索系统，该系统利用GPT-3的知识库（KB）进行问答；在查询时，用户不需要了解产品的特定说明性关键字。我们的方法调谐促使GPT-3的令牌促使知识和渲染答案直接映射到产品的情况下而无需进一步处理。与基线方法相比，我们的方法在两个现实世界和一个公共数据集上显示出一致的性能提高。我们提供了有关将GPT-3知识用于基于问答的检索系统的深入讨论。
As online merchandise become more common, many studies focus on embedding-based methods where queries and products are represented in the semantic space. These methods alleviate the problem of vocab mismatch between the language of queries and products. However, past studies usually dealt with queries that precisely describe the product, and there still exists the need to answer imprecise queries that may require common sense knowledge, i.e., 'what should I get my mom for Mother's Day.' In this paper, we propose a GPT-3 based product retrieval system that leverages the knowledge-base (KB) of GPT-3 for question answering; users do not need to know the specific illustrative keywords for a product when querying. Our method tunes prompt tokens of GPT-3 to prompt knowledge and render answers that are mapped directly to products without further processing. Our method shows consistent performance improvement on two real-world and one public dataset, compared to the baseline methods. We provide an in-depth discussion on leveraging GPT-3 knowledge into a question answering based retrieval system.
