activity
20142023
most citedDeep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey

65 citations · 582 across the 89 of their papers we have counts for

collaborators
Showing 2020Show all

13 papers · 1 filter

cs.CL2020★ 34 cited

Medical Entity Linking using Triplet Network

Ishani Mondal, Sukannya Purkayastha, Sudeshna Sarkar +4

Entity linking (or Normalization) is an essential task in text mining that maps the entity mentions in the medical text to standard entities in a given Knowledge Base (KB). This ta…

cs.CL2020

HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection

Binny Mathew, Punyajoy Saha, Seid Muhie Yimam +3

Hate speech is a challenging issue plaguing the online social media. While better models for hate speech detection are continuously being developed, there is little research on the…

cs.LG2020

Finding Prerequisite Relations between Concepts using Textbook

Shivam Pal, Vipul Arora, Pawan Goyal

A prerequisite is anything that you need to know or understand first before attempting to learn or understand something new. In the current work, we present a method of finding pre…

cs.CL2020

Hierarchical Transformer for Task Oriented Dialog Systems

Bishal Santra, Potnuru Anusha, Pawan Goyal

Generative models for dialog systems have gained much interest because of the recent success of RNN and Transformer based models in tasks like question answering and summarization.…

cs.CL2020

MatScIE: An automated tool for the generation of databases of methods and parameters used in the computational materials science literature

Souradip Guha, Ankan Mullick, Jatin Agrawal +5

The number of published articles in the field of materials science is growing rapidly every year. This comparatively unstructured data source, which contains a large amount of info…

cs.LG2020★ 2 cited

OccamNet: A Fast Neural Model for Symbolic Regression at Scale

Owen Dugan, Rumen Dangovski, Allan Costa +4

Neural networks' expressiveness comes at the cost of complex, black-box models that often extrapolate poorly beyond the domain of the training dataset, conflicting with the goal of…