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20182026
most citedComposition-based Multi-Relational Graph Convolutional Networks

136 citations · 466 across the 24 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.CL2019★ 6 cited

A Re-evaluation of Knowledge Graph Completion Methods

Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal +2

Knowledge Graph Completion (KGC) aims at automatically predicting missing links for large-scale knowledge graphs. A vast number of state-of-the-art KGC techniques have got publishe…

cs.LG2019★ 136 cited

Composition-based Multi-Relational Graph Convolutional Networks

Shikhar Vashishth, Soumya Sanyal, Vikram Nitin +1

Graph Convolutional Networks (GCNs) have recently been shown to be quite successful in modeling graph-structured data. However, the primary focus has been on handling simple undire…

cs.CL2019★ 11 cited

Neural Graph Embedding Methods for Natural Language Processing

Shikhar Vashishth

Knowledge graphs are structured representations of facts in a graph, where nodes represent entities and edges represent relationships between them. Recent research has resulted in…

cs.LG2019★ 4 cited

InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

Shikhar Vashishth, Soumya Sanyal, Vikram Nitin +2

Most existing knowledge graphs suffer from incompleteness, which can be alleviated by inferring missing links based on known facts. One popular way to accomplish this is to generat…

cs.CL2019★ 69 cited

Attention Interpretability Across NLP Tasks

Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar +1

The attention layer in a neural network model provides insights into the model's reasoning behind its prediction, which are usually criticized for being opaque. Recently, seemingly…

cs.LG2019★ 23 cited

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning

Shikhar Vashishth, Prateek Yadav, Manik Bhandari +1

Predicting properties of nodes in a graph is an important problem with applications in a variety of domains. Graph-based Semi-Supervised Learning (SSL) methods aim to address this…

cs.CL2019★ 1 cited

Dating Documents using Graph Convolution Networks

Shikhar Vashishth, Shib Sankar Dasgupta, Swayambhu Nath Ray +1

Document date is essential for many important tasks, such as document retrieval, summarization, event detection, etc. While existing approaches for these tasks assume accurate know…

cs.IR2019★ 77 cited

CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information

Shikhar Vashishth, Prince Jain, Partha Talukdar

Open Information Extraction (OpenIE) methods extract (noun phrase, relation phrase, noun phrase) triples from text, resulting in the construction of large Open Knowledge Bases (Ope…