Providing Insights for Open-Response Surveys via End-to-End Context-Aware Clustering
Teachers often conduct surveys in order to collect data from a predefined group of students to gain insights into topics of interest. When analyzing surveys with open-ended textual responses, it is extremely time-consuming, labor-intensive, and difficult to manually process all the responses into an insightful and comprehensive report. In the analysis step, traditionally, the teacher has to read each of the responses and decide on how to group them in order to extract insightful information. Even though it is possible to group the responses only using certain keywords, such an approach would…
Whether placing an order, requesting a product exchange or asking about a billing concern, today’s customer demands an exceptional experience that includes quick, thorough answers to their inquiries. They also expect service to be delivered 24/7 across multiple channels. While traditional AI approaches provide customers with quick service, they have…
We introduce Anthology, a method for conditioning LLMs to representative, consistent, and diverse virtual personas by generating and utilizing naturalistic backstories with rich details of individual values and experience. What does it mean for large language models (LLMs) to be trained on massive text corpora, collectively produced by millions and…