A System for Human-AI collaboration for Online Customer Support
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Abstract (arXiv)
AI enabled chat bots have recently been put to use to answer customer service queries, however it is a common feedback of users that bots lack a personal touch and are often unable to understand the real intent of the user's question. To this end, it is desirable to have human involvement in the customer servicing process. In this work, we present a system where a human support agent collaborates in real-time with an AI agent to satisfactorily answer customer queries. We describe the user interaction elements of the solution, along with the machine learning techniques involved in the AI agent.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 10 of its 18 references that are in the map. First posted on arXiv 28 Jan 2023.
Builds on
10 of 18 references.
References · 10
- 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
- 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,895
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- 2018QuAC : Question Answering in Contextcited by 379
- 2015The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systemscited by 172
- 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
- 2020DoQA -- Accessing Domain-Specific FAQs via Conversational QAcited by 42
- 2021GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrievalcited by 39
- 2015A Survey of Available Corpora for Building Data-Driven Dialogue Systemscited by 33
- 2021A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysiscited by 4
Built on by
Citing papers per year: 2025: 1; 2026: 2.
3 papers.