Zobrazeno 1 - 10
of 4 344
pro vyhledávání: '"A. Khan, Mohammed"'
Large Language Models (LLMs) are increasingly relied upon to evaluate text outputs of other LLMs, thereby influencing leaderboards and development decisions. However, concerns persist over the accuracy of these assessments and the potential for misle
Externí odkaz:
http://arxiv.org/abs/2406.13439
Autor:
Khan, Mohammed Abdul Hafeez, Ganeriwala, Parth, Bhattacharyya, Siddhartha, Neogi, Natasha, Muthalagu, Raja
Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or pixel-wise segmentations for object localization. Traditional labeling methods, such as crowd-sourcing
Externí odkaz:
http://arxiv.org/abs/2406.08775
Autor:
Aggarwal, Aaveg, Chen, Shih-Yuan, Kirkinis, Eleftherios, Khan, Mohammed Imran, Fan, Bei, Driscoll, Michelle M, de la Cruz, Monica Olvera
Active components incorporated in materials generate motion by inducing conformational changes in response to external fields. Magnetic fields are particularly interesting as they can actuate materials remotely. Millimeter-sized ferrofluid droplets p
Externí odkaz:
http://arxiv.org/abs/2406.08289
Autor:
S, Selva Kumar, Khan, Afifah Khan Mohammed Ajmal, Banday, Imadh Ajaz, Gada, Manikantha, Shanbhag, Vibha Venkatesh
This research introduces an innovative AI-driven precision agriculture system, leveraging YOLOv8 for disease identification and Retrieval Augmented Generation (RAG) for context-aware diagnosis. Focused on addressing the challenges of diseases affecti
Externí odkaz:
http://arxiv.org/abs/2405.01310
This research focused on the development of a cost-effective IoT solution for energy and environment monitoring geared towards manufacturing industries. The proposed system is developed using open-source software that can be easily deployed in any ma
Externí odkaz:
http://arxiv.org/abs/2404.11771
Autor:
Khan, Mohammed Safi Ur Rahman, Mehta, Priyam, Sankar, Ananth, Kumaravelan, Umashankar, Doddapaneni, Sumanth, G, Suriyaprasaad, G, Varun Balan, Jain, Sparsh, Kunchukuttan, Anoop, Kumar, Pratyush, Dabre, Raj, Khapra, Mitesh M.
Despite the considerable advancements in English LLMs, the progress in building comparable models for other languages has been hindered due to the scarcity of tailored resources. Our work aims to bridge this divide by introducing an expansive suite o
Externí odkaz:
http://arxiv.org/abs/2403.06350
Autor:
Gala, Jay, Jayakumar, Thanmay, Husain, Jaavid Aktar, M, Aswanth Kumar, Khan, Mohammed Safi Ur Rahman, Kanojia, Diptesh, Puduppully, Ratish, Khapra, Mitesh M., Dabre, Raj, Murthy, Rudra, Kunchukuttan, Anoop
We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi. Airavata was created by fine-tuning OpenHathi with diverse, instruction-tuning Hindi datasets to make it better suited for assistive tasks. Along with the model, we al
Externí odkaz:
http://arxiv.org/abs/2401.15006
In the contemporary digital era, the Internet functions as an unparalleled catalyst, dismantling geographical and linguistic barriers particularly evident in texting. This evolution facilitates global communication, transcending physical distances an
Externí odkaz:
http://arxiv.org/abs/2401.04619
Publikováno v:
International Journal of Numerical Methods for Heat & Fluid Flow, 2024, Vol. 34, Issue 8, pp. 3131-3165.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/HFF-09-2023-0568
V2X (Vehicle-to-everything) communication relies on short messages for short-range transmissions over a fading wireless channel, yet requires high reliability and low latency. Hard-decision decoding sacrifices the preservation of diversity order, lea
Externí odkaz:
http://arxiv.org/abs/2304.03561