Zobrazeno 1 - 8
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pro vyhledávání: '"Marathe, Manisha"'
This paper describes the approach to the Emotion Classification shared task held at WASSA 2022 by team PVGs AI Club. This Track 2 sub-task focuses on building models which can predict a multi-class emotion label based on essays from news articles whe
Externí odkaz:
http://arxiv.org/abs/2205.00283
Transformer based language models have led to impressive results across all domains in Natural Language Processing. Pretraining these models on language modeling tasks and finetuning them on downstream tasks such as Text Classification, Question Answ
Externí odkaz:
http://arxiv.org/abs/2112.01742
Since their inception, transformer-based language models have led to impressive performance gains across multiple natural language processing tasks. For Arabic, the current state-of-the-art results on most datasets are achieved by the AraBERT languag
Externí odkaz:
http://arxiv.org/abs/2103.05683
Active research pertaining to the affective phenomenon of empathy and distress is invaluable for improving human-machine interaction. Predicting intensities of such complex emotions from textual data is difficult, as these constructs are deeply roote
Externí odkaz:
http://arxiv.org/abs/2103.03296
Autor:
Kulkarni, Hrishikesh, Marathe, Manisha
Publikováno v:
International Journal of Information and Decision Sciences; 2020, Vol. 12 Issue: 3 p211-226, 16p
Autor:
Marathe, Manisha
Publikováno v:
Clinical Dentistry (0974-3979); Feb2018, Vol. 12 Issue 2, p10-15, 6p
Publikováno v:
International Journal of Recent Trends in Engineering; Nov2009, Vol. 2 Issue 4, p62-64, 3p
Publikováno v:
Proceedings of the International Conference & Workshop: Emerging Trends in Technology; 2/26/2010, p1023-1023, 1p