Faisal Ahmad

Also published as: Faisal Ahmed


Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access
Bhuwan Dhingra | Lihong Li | Xiujun Li | Jianfeng Gao | Yun-Nung Chen | Faisal Ahmed | Li Deng
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

This paper proposes KB-InfoBot - a multi-turn dialogue agent which helps users search Knowledge Bases (KBs) without composing complicated queries. Such goal-oriented dialogue agents typically need to interact with an external database to access real-world knowledge. Previous systems achieved this by issuing a symbolic query to the KB to retrieve entries based on their attributes. However, such symbolic operations break the differentiability of the system and prevent end-to-end training of neural dialogue agents. In this paper, we address this limitation by replacing symbolic queries with an induced “soft” posterior distribution over the KB that indicates which entities the user is interested in. Integrating the soft retrieval process with a reinforcement learner leads to higher task success rate and reward in both simulations and against real users. We also present a fully neural end-to-end agent, trained entirely from user feedback, and discuss its application towards personalized dialogue agents.


Pedagogically Useful Extractive Summaries for Science Education
Sebastian de la Chica | Faisal Ahmad | James H. Martin | Tamara Sumner
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

Extractive Summaries for Educational Science Content
Sebastian de la Chica | Faisal Ahmad | James H. Martin | Tamara Sumner
Proceedings of ACL-08: HLT, Short Papers