Learning Personalized User Preference from Cold Start in Multi-turn Conversations

no code implementations • 10 Sep 2023 • Deguang Kong, Abhay Jha, Lei Yun

This paper presents a novel teachable conversation interaction system that is capable of learning users preferences from cold start by gradually adapting to personal preferences.

named-entity-recognition Named Entity Recognition +1

Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems

no code implementations • NAACL 2021 • Anish Acharya, Suranjit Adhikari, Sanchit Agarwal, Vincent Auvray, Nehal Belgamwar, Arijit Biswas, Shubhra Chandra, Tagyoung Chung, Maryam Fazel-Zarandi, Raefer Gabriel, Shuyang Gao, Rahul Goel, Dilek Hakkani-Tur, Jan Jezabek, Abhay Jha, Jiun-Yu Kao, Prakash Krishnan, Peter Ku, Anuj Goyal, Chien-Wei Lin, Qing Liu, Arindam Mandal, Angeliki Metallinou, Vishal Naik, Yi Pan, Shachi Paul, Vittorio Perera, Abhishek Sethi, Minmin Shen, Nikko Strom, Eddie Wang

Finally, we evaluate our system using a typical movie ticket booking task and show that the dialogue simulator is an essential component of the system that leads to over $50\%$ improvement in turn-level action signature prediction accuracy.

Dialogue State Tracking Goal-Oriented Dialogue Systems +3

Lifted Inference Seen from the Other Side : The Tractable Features

no code implementations • NeurIPS 2010 • Abhay Jha, Vibhav Gogate, Alexandra Meliou, Dan Suciu

Lifted inference algorithms for representations that combine first-order logic and probabilistic graphical models have been the focus of much recent research.