Search Results for author: Rashmi Gangadharaiah

Found 14 papers, 0 papers with code

PerKGQA: Question Answering over Personalized Knowledge Graphs

no code implementations Findings (NAACL) 2022 Ritam Dutt, Kasturi Bhattacharjee, Rashmi Gangadharaiah, Dan Roth, Carolyn Rose

The above concerns motivate our question answer- ing setting over personalized knowledge graphs (PERKGQA) where each user has restricted access to their KG.

Knowledge Graphs Question Answering

What Do Users Care About? Detecting Actionable Insights from User Feedback

no code implementations NAACL (ACL) 2022 Kasturi Bhattacharjee, Rashmi Gangadharaiah, Kathleen McKeown, Dan Roth

Users often leave feedback on a myriad of aspects of a product which, if leveraged successfully, can help yield useful insights that can lead to further improvements down the line.

Recursive Template-based Frame Generation for Task Oriented Dialog

no code implementations ACL 2020 Rashmi Gangadharaiah, Balakrishnan Narayanaswamy

The Natural Language Understanding (NLU) component in task oriented dialog systems processes a user{'}s request and converts it into structured information that can be consumed by downstream components such as the Dialog State Tracker (DST).

Natural Language Understanding

What we need to learn if we want to do and not just talk

no code implementations NAACL 2018 Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan

In task-oriented dialog, agents need to generate both fluent natural language responses and correct external actions like database queries and updates.

Chatbot Machine Translation

Achieving Fluency and Coherency in Task-oriented Dialog

no code implementations11 Apr 2018 Rashmi Gangadharaiah, Balakrishnan Narayanaswamy, Charles Elkan

We show how to combine nearest neighbor and Seq2Seq methods in a hybrid model, where nearest neighbor is used to generate fluent responses and Seq2Seq type models ensure dialog coherency and generate accurate external actions.

Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions

no code implementations29 Mar 2013 Niraj Kumar, Rashmi Gangadharaiah, Kannan Srinathan, Vasudeva Varma

Next, we apply an improved version of ranking with a prior-based approach, which ranks all words in the candidate document with respect to a set of root words (i. e. non-stopwords present in the question and in the candidate document).

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