Accepted Paper in AAAI 2022!! Acceptance Rate: 15%

ISEEQ, a joint work with Kalpa Gunaratna, Vijay Srinivasan, and Hongxia Jin will be presented at AAAI 2022

Preface:

1. We contributed to broadening the capability of Conversational Information Seeking (CIS) agents by introducing the capability of curiosity through commonsense knowledge graphs.
2. We introduced ISEEQ, a CIS system capable of providing conversational assistance by dynamically retrieving meta-information supportive in generating information-seeking questions (ISQs).
3. In contrast to clarifying or followup questions, ISQs go a step further with expanding the query context by exploring relationships between entities in the query and linked entities in a knowledge graph. Thus retrieve a diverse set of passages to address a user query adequately.
4. ISEEQ opens up future research directions in CIS by facilitating the automatic creation of large-scale datasets to develop and train improved CIS systems. Furthermore, crowd-workers can evaluate and augment such datasets rather than create them anew, thus improving dataset standards.
5. Broadly construed, through reinforcement learning with the reward on conceptual flow and logical agreement, ISEEQ can be trained to generate questions that are safety constrained and follow a specialized knowledge processing. reference