Search Results for author: Nikita Bhutani

Found 10 papers, 3 papers with code

Distilling Salient Reviews with Zero Labels

no code implementations FEVER (ACL) 2022 Chieh-Yang Huang, Jinfeng Li, Nikita Bhutani, Alexander Whedon, Estevam Hruschka, Yoshi Suhara

To alleviate this scarcity problem, we develop an unsupervised method, ZL-Distiller, which leverages contextual language representations of the reviews and their distributional patterns to identify salient sentences about entities.

Question Answering

CompactIE: Compact Facts in Open Information Extraction

1 code implementation5 May 2022 Farima Fatahi Bayat, Nikita Bhutani, H. V. Jagadish

Our experiments on CaRB and Wire57 datasets indicate that CompactIE finds 1. 5x-2x more compact extractions than previous systems, with high precision, establishing a new state-of-the-art performance in OpenIE.

Open Information Extraction

Can Edge Probing Tasks Reveal Linguistic Knowledge in QA Models?

no code implementations15 Sep 2021 Sagnik Ray Choudhury, Nikita Bhutani, Isabelle Augenstein

There have been many efforts to try to understand what gram-matical knowledge (e. g., ability to understand the part of speech of a token) is encoded in large pre-trained language models (LM).

Question Answering

Powering Effective Climate Communication with a Climate Knowledge Base

no code implementations23 Jul 2021 Kameron B. Rodrigues, Shweta Khushu, Mukut Mukherjee, Andrew Banister, Anthony Hevia, Sampath Duddu, Nikita Bhutani

While many accept climate change and its growing impacts, few converse about it well, limiting the adoption speed of societal changes necessary to address it.

Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases

no code implementations WS 2020 Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish

Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.

Question Answering

SubjQA: A Dataset for Subjectivity and Review Comprehension

1 code implementation EMNLP 2020 Johannes Bjerva, Nikita Bhutani, Behzad Golshan, Wang-Chiew Tan, Isabelle Augenstein

We find that subjectivity is also an important feature in the case of QA, albeit with more intricate interactions between subjectivity and QA performance.

Question Answering Sentiment Analysis +1

Sampo: Unsupervised Knowledge Base Construction for Opinions and Implications

1 code implementation AKBC 2020 Nikita Bhutani, Aaron Traylor, Chen Chen, Xiaolan Wang, Behzad Golshan, Wang-Chiew Tan

Since it can be expensive to obtain training data to learn to extract implications for each new domain of reviews, we propose an unsupervised KBC system, Sampo, Specifically, Sampo is tailored to build KBs for domains where many reviews on the same domain are available.

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