Search Results for author: Kapil Thadani

Found 11 papers, 1 papers with code

Powering COVID-19 community Q&A with Curated Side Information

no code implementations27 Jan 2021 Manisha Verma, Kapil Thadani, Shaunak Mishra

In this work, we demonstrate the effectiveness of different attention based neural models that can directly exploit side information available in technical documents or verified forums (e. g., research publications on COVID-19 or WHO website).

Community Question Answering

Effective Few-Shot Classification with Transfer Learning

no code implementations COLING 2020 Aakriti Gupta, Kapil Thadani, Neil O{'}Hare

In this work, we use the ARSC dataset to study a simple application of transfer learning approaches to few-shot classification.

Classification Few-Shot Learning +5

Learning to Create Better Ads: Generation and Ranking Approaches for Ad Creative Refinement

no code implementations17 Aug 2020 Shaunak Mishra, Manisha Verma, Yichao Zhou, Kapil Thadani, Wei Wang

Since major ad platforms typically run A/B tests for multiple advertisers in parallel, we explore the possibility of collaboratively learning ad creative refinement via A/B tests of multiple advertisers.

TAG Text Generation

Extractive Summarization under Strict Length Constraints

no code implementations LREC 2016 Yashar Mehdad, Am Stent, a, Kapil Thadani, Dragomir Radev, Youssef Billawala, Karolina Buchner

In this paper we report a comparison of various techniques for single-document extractive summarization under strict length budgets, which is a common commercial use case (e. g. summarization of news articles by news aggregators).

Extractive Summarization

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