L3Cube-MahaSum: A Comprehensive Dataset and BART Models for Abstractive Text Summarization in Marathi.
Nikita Kulkarni|Kareena Manghani|Sanhita Kulkarni|Pranita Deshmukh|Raviraj Joshi
| Anthology ID: | DBLP:conf/fire/KulkarniMKDJ24 |
|---|---|
| Volume: | Proceedings of the 16th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2024, Gandhinagar, India, December 12-15, 2024 |
| Year: | 2024 |
| Venue: | Forum for Information Retrieval Evaluation (FIRE) |
| Publisher: | ACM |
| Pages: | 76-79 |
| URL: | https://doi.org/10.1145/3734947.3734953 |
| DOI: | https://doi.org/10.1145/3734947.3734953 |
| DBLP: | conf/fire/KulkarniMKDJ24 |
| BibTeX: |
@inproceedings{kulkarni-2024-l3cubemahasum,
author = {Nikita Kulkarni and
Kareena Manghani and
Sanhita Kulkarni and
Pranita Deshmukh and
Raviraj Joshi},
editor = {Debasis Ganguly and
Debarshi Kumar Sanyal and
Prasenjit Majumder and
Srijoni Majumdar and
Surupendu Gangopadhyay},
title = {{L3Cube-MahaSum: A Comprehensive Dataset and BART Models for Abstractive Text Summarization in Marathi}},
booktitle = {{Proceedings of the 16th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2024, Gandhinagar, India, December 12-15, 2024}},
pages = {76--79},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3734947.3734953},
doi = {https://doi.org/10.1145/3734947.3734953}
}