Papers by Sudip Kumar Naskar

2 papers
IndicFinNLP: Financial Natural Language Processing for Indian Languages (2024.lrec-main)

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Challenge: IndicFinNLP is a collection of 9 datasets relating to FinNLP for three Indian languages.
Approach: They propose to use financial NLP to detect exaggerated numerals in financial texts written in Hindi, Bengali, and Telugu.
Outcome: The proposed framework detects exaggerated numerals in financial texts written in Hindi, Bengali, and Telugu.
The Transference Architecture for Automatic Post-Editing (2020.coling-main)

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Challenge: A research challenge is the search for architectures that best support the capture, preparation and provision of src and mt information and its integration with pe decisions.
Approach: They propose a multi-encoder based neural APE model that conditions post-editing decisions on both the source and machine translated text as inputs.
Outcome: The proposed model outperforms the best performing systems by 1 BLEU point on the WMT 2016, 2017, and 2018 English–German APE shared tasks.

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