Search Results for author: Nitish Kulkarni

Found 3 papers, 1 papers with code

AmazonQA: A Review-Based Question Answering Task

1 code implementation12 Aug 2019 Mansi Gupta, Nitish Kulkarni, Raghuveer Chanda, Anirudha Rayasam, Zachary C. Lipton

Observing that many questions can be answered based upon the available product reviews, we propose the task of review-based QA.

Answer Generation Information Retrieval +3

Question Relevance in Visual Question Answering

no code implementations23 Jul 2018 Prakruthi Prabhakar, Nitish Kulkarni, Linghao Zhang

Current VQA systems do not evaluate if the posed question is relevant to the input image and hence provide nonsensical answers when posed with irrelevant questions to an image.

Question Answering Visual Question Answering

BioAMA: Towards an End to End BioMedical Question Answering System

no code implementations WS 2018 Vasu Sharma, Nitish Kulkarni, Srividya Pranavi, Gabriel Bayomi, Eric Nyberg, Teruko Mitamura

In this paper, we present a novel Biomedical Question Answering system, BioAMA: {``}Biomedical Ask Me Anything{''} on task 5b of the annual BioASQ challenge.

Natural Language Inference NER +4

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