activity
20202022
most citedLogical Neural Networks

84 citations · 98 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AI20222 cited

Expressive Reasoning Graph Store: A Unified Framework for Managing RDF and Property Graph Databases

Sumit Neelam, Udit Sharma, Sumit Bhatia +5

Resource Description Framework (RDF) and Property Graph (PG) are the two most commonly used data models for representing, storing, and querying graph data. We present Expressive Re…

cs.CL20221 cited

Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases

Nithish Kannen, Udit Sharma, Sumit Neelam +4

Knowledge Base Question Answering (KBQA) systems have the goal of answering complex natural language questions by reasoning over relevant facts retrieved from Knowledge Bases (KB).…

cs.CL20227 cited

A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases

Sumit Neelam, Udit Sharma, Hima Karanam +22

Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…

cs.CL20214 cited

SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases

Sumit Neelam, Udit Sharma, Hima Karanam +21

Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…

cs.CL2021

LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking

Hang Jiang, Sairam Gurajada, Qiuhao Lu +5

Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a knowledge graph, is crucial for text understanding, question answering or conversa…

cs.CL2020

Leveraging Abstract Meaning Representation for Knowledge Base Question Answering

Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar +27

Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understandin…