Kyle Williams

According to our database, Kyle Williams authored at least 8 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

MedicalSum: A Guided Clinical Abstractive Summarization Model for Generating Medical Reports from Patient-Doctor Conversations.

George Michalopoulos, Kyle Williams, Gagandeep Singh, Thomas Lin

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2019

Automatic Task Completion Flows from Web APIs.

Kyle Williams, Seyyed Hadi Hashemi, Imed Zitouni

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Neural Lexicons for Slot Tagging in Spoken Language Understanding.

Kyle Williams

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Zero Shot Intent Classification Using Long-Short Term Memory Networks.

Kyle Williams

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Slot Tagging for Task Oriented Spoken Language Understanding in Human-to-Human Conversation Scenarios.

Kunho Kim, Rahul Jha, Kyle Williams, Alex Marin, Imed Zitouni

Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019

2018

Impact of Domain and User's Learning Phase on Task and Session Identification in Smart Speaker Intelligent Assistants.

Seyyed Hadi Hashemi, Kyle Williams, Ahmed El Kholy, Imed Zitouni, Paul A. Crook

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Measuring User Satisfaction on Smart Speaker Intelligent Assistants Using Intent Sensitive Query Embeddings.

Seyyed Hadi Hashemi, Kyle Williams, Ahmed El Kholy, Imed Zitouni, Paul A. Crook

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Does That Mean You're Happy?: RNN-based Modeling of User Interaction Sequences to Detect Good Abandonment.

Kyle Williams, Imed Zitouni

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017