activity
20182021
most citedALLWAS: Active Learning on Language models in WASserstein space

1 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20211 cited

ALLWAS: Active Learning on Language models in WASserstein space

Anson Bastos, Manohar Kaul

Active learning has emerged as a standard paradigm in areas with scarcity of labeled training data, such as in the medical domain. Language models have emerged as the prevalent cho…

cs.IR20211 cited

HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations

Anson Bastos, Kuldeep Singh, Abhishek Nadgeri +3

Recently, several Knowledge Graph Embedding (KGE) approaches have been devised to represent entities and relations in dense vector space and employed in downstream tasks such as li…

cs.CL20211 cited

KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

Abhishek Nadgeri, Anson Bastos, Kuldeep Singh +4

We present a novel method for relation extraction (RE) from a single sentence, mapping the sentence and two given entities to a canonical fact in a knowledge graph (KG). Especially…

cs.CL2020

RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network

Anson Bastos, Abhishek Nadgeri, Kuldeep Singh +4

In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG). R…

cs.CL2018

Learning sentence embeddings using Recursive Networks

Anson Bastos

Learning sentence vectors that generalise well is a challenging task. In this paper we compare three methods of learning phrase embeddings: 1) Using LSTMs, 2) using recursive nets,…