Papers by Suchetha Nambanoor Kunnath

2 papers
Dynamic Context Extraction for Citation Classification (2022.aacl-main)

Copied to clipboard

Challenge: Prior studies have focused on the application of fixed-size contiguous citation contexts or manually curated citation contextual contexts.
Approach: They propose an automated unsupervised approach for the selection of a dynamic-size and potentially non-contiguous citation context based on transformer-based document representations and embedding similarities.
Outcome: The proposed model improves on the domain-specific and multi-disciplinary datasets, irrespective of the dataset's domain.
ACT2: A multi-disciplinary semi-structured dataset for importance and purpose classification of citations (2022.lrec-1)

Copied to clipboard

Challenge: Existing methods for classifying citations rely on bibliometric measures to consider the semantics of citation.
Approach: They propose to use a Citation Context Classification (3C) shared task dataset to classify citations according to their purpose and importance.
Outcome: The proposed model can be used to link research works to graphs and enable efficient knowledge discovery.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations