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20162025
most citedA Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases

7 citations · 18 across the 6 of their papers we have counts for

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cs.CL2023

Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems

Aniruddha Deb, Neeva Oza, Sarthak Singla +3

While forward reasoning (i.e., find the answer given the question) has been explored extensively in recent literature, backward reasoning is relatively unexplored. We examine the b…

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.CL20213 cited

Knowledge Graph Question Answering via SPARQL Silhouette Generation

Sukannya Purkayastha, Saswati Dana, Dinesh Garg +2

Knowledge Graph Question Answering (KGQA) has become a prominent area in natural language processing due to the emergence of large-scale Knowledge Graphs (KGs). Recently Neural Mac…

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…