42 citations · 42 across the 2 of their papers we have counts for
8 papers
Mix-and-Match: Scalable Dialog Response Retrieval using Gaussian Mixture Embeddings
Gaurav Pandey, Danish Contractor, Sachindra Joshi
Embedding-based approaches for dialog response retrieval embed the context-response pairs as points in the embedding space. These approaches are scalable, but fail to account for t…
It's Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Process
Brent Hecht, Lauren Wilcox, Jeffrey P. Bigham +9
The computing research community needs to work much harder to address the downsides of our innovations. Between the erosion of privacy, threats to democracy, and automation's effec…
Joint Spatio-Textual Reasoning for Answering Tourism Questions
Danish Contractor, Shashank Goel, Mausam +1
Our goal is to answer real-world tourism questions that seek Points-of-Interest (POI) recommendations. Such questions express various kinds of spatial and non-spatial constraints,…
Simulated Chats for Building Dialog Systems: Learning to Generate Conversations from Instructions
Biswesh Mohapatra, Gaurav Pandey, Danish Contractor +1
Popular dialog datasets such as MultiWOZ are created by providing crowd workers an instruction, expressed in natural language, that describes the task to be accomplished. Crowd wor…
Neural Conversational QA: Learning to Reason v.s. Exploiting Patterns
Nikhil Verma, Abhishek Sharma, Dhiraj Madan +3
Neural Conversational QA tasks like ShARC require systems to answer questions based on the contents of a given passage. On studying recent state-of-the-art models on the ShARCQA ta…
Large Scale Question Answering using Tourism Data
Danish Contractor, Krunal Shah, Aditi Partap +2
We introduce the novel task of answering entity-seeking recommendation questions using a collection of reviews that describe candidate answer entities. We harvest a QA dataset that…