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pro vyhledávání: '"Arora Gaurav"'
Reasoning and linguistic skills form the cornerstone of human intelligence, facilitating problem-solving and decision-making. Recent advances in Large Language Models (LLMs) have led to impressive linguistic capabilities and emergent reasoning behavi
Externí odkaz:
http://arxiv.org/abs/2410.14235
Intent detection is a critical component of task-oriented dialogue systems (TODS) which enables the identification of suitable actions to address user utterances at each dialog turn. Traditional approaches relied on computationally efficient supervis
Externí odkaz:
http://arxiv.org/abs/2410.01627
Autor:
Sani, Depanshu, Mahato, Sandeep, Saini, Sourabh, Agarwal, Harsh Kumar, Devshali, Charu Chandra, Anand, Saket, Arora, Gaurav, Jayaraman, Thiagarajan
The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite greater access to earth observation data in agriculture, there is a scarcity of curated and labelled datasets, which limits the potential of its
Externí odkaz:
http://arxiv.org/abs/2312.00069
Autor:
Arora, Gaurav1,2 (AUTHOR) gaurav@iiitd.ac.in, Feng, Hongli3 (AUTHOR)
Publikováno v:
Scientific Reports. 11/4/2024, Vol. 14 Issue 1, p1-17. 17p.
Autor:
Sani, Depanshu, Mahato, Sandeep, Sirohi, Parichya, Anand, Saket, Arora, Gaurav, Devshali, Charu Chandra, Jayaraman, Thiagarajan, Agarwal, Harsh Kumar
The availability of well-curated datasets has driven the success of Machine Learning (ML) models. Despite the increased access to earth observation data for agriculture, there is a scarcity of curated, labelled datasets, which limits the potential of
Externí odkaz:
http://arxiv.org/abs/2209.12238
Autor:
Sani, Depanshu, Mahato, Sandeep, Sirohi, Parichya, Anand, Saket, Arora, Gaurav, Devshali, Charu Chandra, Jayaraman, T.
The integration of the modern Machine Learning (ML) models into remote sensing and agriculture has expanded the scope of the application of satellite images in the agriculture domain. In this paper, we present how the accuracy of crop type identifica
Externí odkaz:
http://arxiv.org/abs/2205.03104
Autor:
Haack, Lindsey, Das, Nikkan, Hoskoppal, Arvind, DeBrunner, Mark, Alsaied, Tarek, Arora, Gaurav
Publikováno v:
In The Journal of Pediatrics February 2024 265
Publikováno v:
In Journal of Engineering Research April 2024
Autor:
Arora, Gaurav
This paper describes the system submitted to Dravidian-Codemix-HASOC2020: Hate Speech and Offensive Content Identification in Dravidian languages (Tamil-English and Malayalam-English). The task aims to identify offensive language in code-mixed datase
Externí odkaz:
http://arxiv.org/abs/2010.02094
Publikováno v:
Proceedings of the First Workshop on Insights from Negative Results in NLP @ EMNLP 2020
Intent Detection systems in the real world are exposed to complexities of imbalanced datasets containing varying perception of intent, unintended correlations and domain-specific aberrations. To facilitate benchmarking which can reflect near real-wor
Externí odkaz:
http://arxiv.org/abs/2009.13833