Search Results for author: Dhanasekar Sundararaman

Found 7 papers, 2 papers with code

Learning Task Sampling Policy for Multitask Learning

no code implementations Findings (EMNLP) 2021 Dhanasekar Sundararaman, Henry Tsai, Kuang-Huei Lee, Iulia Turc, Lawrence Carin

It has been shown that training multi-task models with auxiliary tasks can improve the target task quality through cross-task transfer.

reinforcement-learning

Number Entity Recognition

no code implementations7 May 2022 Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Liyan Xu, Lawrence Carin

Numbers are essential components of text, like any other word tokens, from which natural language processing (NLP) models are built and deployed.

Question Answering

Learning Compressed Sentence Representations for On-Device Text Processing

1 code implementation ACL 2019 Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman, Xinyuan Zhang, Qian Yang, Meng Tang, Asli Celikyilmaz, Lawrence Carin

Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems.

Sentence Embeddings

Cannot find the paper you are looking for? You can Submit a new open access paper.