no code implementations • 13 Sep 2022 • Bhargav Dodla, Akash Kumar Mohankumar, Amit Singh
Matching user search queries with relevant keywords bid by advertisers in real-time is a crucial problem in sponsored search.
1 code implementation • ACL 2022 • Akash Kumar Mohankumar, Mitesh M. Khapra
In this work, we introduce Active Evaluation, a framework to efficiently identify the top-ranked system by actively choosing system pairs for comparison using dueling bandit algorithms.
no code implementations • 7 Jun 2021 • Akash Kumar Mohankumar, Nikit Begwani, Amit Singh
For head and torso search queries, sponsored search engines use a huge repository of same intent queries and keywords, mined ahead of time.
1 code implementation • 23 Sep 2020 • Ananya B. Sai, Akash Kumar Mohankumar, Siddhartha Arora, Mitesh M. Khapra
However, no such data is publicly available, and hence existing models are usually trained using a single relevant response and multiple randomly selected responses from other contexts (random negatives).
no code implementations • 27 Aug 2020 • Ananya B. Sai, Akash Kumar Mohankumar, Mitesh M. Khapra
The expanding number of NLG models and the shortcomings of the current metrics has led to a rapid surge in the number of evaluation metrics proposed since 2014.
2 code implementations • ACL 2020 • Akash Kumar Mohankumar, Preksha Nema, Sharan Narasimhan, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran
To make attention mechanisms more faithful and plausible, we propose a modified LSTM cell with a diversity-driven training objective that ensures that the hidden representations learned at different time steps are diverse.
1 code implementation • IJCNLP 2019 • Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra, Balaji Vasan Srinivasan, Balaraman Ravindran
It is desired that the generated question should be (i) grammatically correct (ii) answerable from the passage and (iii) specific to the given answer.