Pranav Shetty
Orcid: 0000-0003-2015-9556
According to our database1,
Pranav Shetty
authored at least 14 papers
between 2021 and 2025.
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Bibliography
2025
A pipeline for data and knowledge extraction from material science literature to accelerate scientific discovery.
PhD thesis, 2025
Where is this coming from? Making groundedness count in the evaluation of Document VQA models.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
Accelerating materials discovery for polymer solar cells: Data-driven insights enabled by natural language processing.
CoRR, 2024
POLYIE: A Dataset of Information Extraction from Polymer Material Scientific Literature.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
"What is the value of templates?" Rethinking Document Information Extraction Datasets for LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
2023
A Compact Quad-Port UWB MIMO Antenna With Improved Isolation Using a Novel Mesh-Like Decoupling Structure and Unique DGS.
IEEE Trans. Circuits Syst. II Express Briefs, March, 2023
2022
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images.
CoRR, 2022
A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language Processing.
CoRR, 2022
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning.
CoRR, 2022
Design of a Six-Port Compact UWB MIMO Antenna With a Distinctive DGS for Improved Isolation.
IEEE Access, 2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
2021
Machine-Guided Polymer Knowledge Extraction Using Natural Language Processing: The Example of Named Entity Normalization.
J. Chem. Inf. Model., 2021
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021