Papers by Alif Munim
Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support (2022.emnlp-industry)
Copied to clipboard
Stephen Obadinma, Faiza Khan Khattak, Shirley Wang, Tania Sidhorn, Elaine Lau, Sean Robertson, Jingcheng Niu, Winnie Au, Alif Munim, Karthik Raja Kalaiselvi Bhaskar
| Challenge: | Creating agent assistants that can help improve customer service support requires inputs from industry users and their customers as well as knowledge of state-of-the-art natural language processing (NLP) technology. |
| Approach: | They propose to combine expertise from academia and industry to build task/domain-specific Neural Agent Assistants with three high-level components for: (1) Intent Identification, (2) Context Retrieval, and (3) Response Generation. |
| Outcome: | The proposed framework is based on three case studies of industry partners who successfully adapt the framework to their unique challenges. |