1 citations · 1 across the 3 of their papers we have counts for
3 papers
RetinaQA: A Robust Knowledge Base Question Answering Model for both Answerable and Unanswerable Questions
Prayushi Faldu, Indrajit Bhattacharya, Mausam
An essential requirement for a real-world Knowledge Base Question Answering (KBQA) system is the ability to detect the answerability of questions when generating logical forms. How…
Neuro-symbolic Meta Reinforcement Learning for Trading
S I Harini, Gautam Shroff, Ashwin Srinivasan +2
We model short-duration (e.g. day) trading in financial markets as a sequential decision-making problem under uncertainty, with the added complication of continual concept-drift. W…
Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions
Mayur Patidar, Prayushi Faldu, Avinash Singh +3
When answering natural language questions over knowledge bases, missing facts, incomplete schema and limited scope naturally lead to many questions being unanswerable. While answer…