33 citations · 34 across the 6 of their papers we have counts for
5 papers · 1 filter
A Grounded and Decomposed Framework for Relation-Level Hallucination Evaluation in Abstractive Summarization
Praveen Kumar Katwe, Rakesh Chandra Balabantaray, Kali Prasad Vittala +1
Abstractive text summarization systems frequently generate fluent yet unfaithful summaries by fabricating or distorting relationships between entities and events. Such relation-lev…
Abstractiveness Metrics for Evaluating Text Summarization: A Refined Formulation with Empirical Validation
Praveenkumar Katwe, Rakesh Chandra Balabantaray, Kali Prasad Vittala
Quantifying abstractiveness in generated summaries is essential for evaluating summarization models beyond surface-level metrics like ROUGE. We introduce Reference Abstraction (RA)…
Bridging the Data Gap: Creating a Hindi Text Summarization Dataset from the English XSUM
Praveenkumar Katwe, RakeshChandra Balabantaray, Kaliprasad Vittala
Current advancements in Natural Language Processing (NLP) have largely favored resource-rich languages, leaving a significant gap in high-quality datasets for low-resource language…
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages
Sankalp Bahad, Pruthwik Mishra, Karunesh Arora +3
Named Entity Recognition (NER) is a useful component in Natural Language Processing (NLP) applications. It is used in various tasks such as Machine Translation, Summarization, Info…
Automatic Parallel Corpus Creation for Hindi-English News Translation Task
Aditya Kumar Pathak, Priyankit Acharya, Dilpreet Kaur +1
The parallel corpus for multilingual NLP tasks, deep learning applications like Statistical Machine Translation Systems is very important. The parallel corpus of Hindi-English lang…