65 citations · 121 across the 16 of their papers we have counts for
4 papers · 2 filters
Adapting Pre-trained Generative Models for Extractive Question Answering
Prabir Mallick, Tapas Nayak, Indrajit Bhattacharya
Pre-trained Generative models such as BART, T5, etc. have gained prominence as a preferred method for text generation in various natural language processing tasks, including abstra…
Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks?
Pratik Saini, Tapas Nayak, Indrajit Bhattacharya
Two distinct approaches have been proposed for relational triple extraction - pipeline and joint. Joint models, which capture interactions across triples, are the more recent devel…
FinRED: A Dataset for Relation Extraction in Financial Domain
Soumya Sharma, Tapas Nayak, Arusarka Bose +4
Relation extraction models trained on a source domain cannot be applied on a different target domain due to the mismatch between relation sets. In the current literature, there is…
90% F1 Score in Relational Triple Extraction: Is it Real ?
Pratik Saini, Samiran Pal, Tapas Nayak +1
Extracting relational triples from text is a crucial task for constructing knowledge bases. Recent advancements in joint entity and relation extraction models have demonstrated rem…