Zobrazeno 1 - 10
of 5 267
pro vyhledávání: '"Rengarajan A."'
Publikováno v:
E3S Web of Conferences, Vol 540, p 02021 (2024)
This paper meticulously reviews the work in the realms of Smart Mobility and Electric Vehicles (EVs) integration within the framework of Smart Cities, aiming to foster sustainable transportation solutions. The discourse delves into the broad areas of
Externí odkaz:
https://doaj.org/article/f12b115757934145800955f989287832
Publikováno v:
E3S Web of Conferences, Vol 540, p 08010 (2024)
As the quest for intelligent and eco-friendly urban progress gains momentum, the integration of renewable energy resources within smart city infrastructures becomes increasingly pivotal. This comprehensive review article delves into the confluence of
Externí odkaz:
https://doaj.org/article/cb9f93d7a92642a491116278913ec60e
Autor:
Gupta, Pranav, Rengarajan, Rishabh, Bankapur, Viren, Mannem, Vedansh, Ahuja, Lakshit, Vijay, Surya, Wang, Kevin
Publikováno v:
Curieux Academic Journal Part 2 Issue 43 (2024), pp. 626-634
Combining LiDAR and Camera-view data has become a common approach for 3D Object Detection. However, previous approaches combine the two input streams at a point-level, throwing away semantic information derived from camera features. In this paper we
Externí odkaz:
http://arxiv.org/abs/2410.11211
Autor:
Montalan, Jann Railey, Ngui, Jian Gang, Leong, Wei Qi, Susanto, Yosephine, Rengarajan, Hamsawardhini, Tjhi, William Chandra, Aji, Alham Fikri
Multilingual large language models (LLMs) today may not necessarily provide culturally appropriate and relevant responses to its Filipino users. We introduce Kalahi, a cultural LLM evaluation suite collaboratively created by native Filipino speakers.
Externí odkaz:
http://arxiv.org/abs/2409.15380
Autor:
Naug, Avisek, Guillen, Antonio, Luna, Ricardo, Gundecha, Vineet, Rengarajan, Desik, Ghorbanpour, Sahand, Mousavi, Sajad, Babu, Ashwin Ramesh, Markovikj, Dejan, Kashyap, Lekhapriya D, Sarkar, Soumyendu
Machine learning has driven an exponential increase in computational demand, leading to massive data centers that consume significant amounts of energy and contribute to climate change. This makes sustainable data center control a priority. In this p
Externí odkaz:
http://arxiv.org/abs/2408.07841
Autor:
Jha, Sumit Kumar, Mishra, Purnendu, Mathur, Shubham, Singh, Gursewak, Kumar, Rajiv, Aatre, Kiran, Rengarajan, Suraj
Immunohistochemistry (IHC) analysis is a well-accepted and widely used method for molecular subtyping, a procedure for prognosis and targeted therapy of breast carcinoma, the most common type of tumor affecting women. There are four molecular biomark
Externí odkaz:
http://arxiv.org/abs/2406.10893
Autor:
Donovan, Peter, Jellum, Erling, Jun, Byeonggil, Kim, Hokeun, Lee, Edward A., Lin, Shaokai, Lohstroh, Marten, Rengarajan, Anirudh
Discrete-event (DE) systems are concurrent programs where components communicate via tagged events, where tags are drawn from a totally ordered set. Reactors are an emerging model of computation based on DE and realized in the open-source coordinatio
Externí odkaz:
http://arxiv.org/abs/2405.12117
Autor:
Bura, Archana, Bobbili, Sarat Chandra, Rameshkumar, Shreyas, Rengarajan, Desik, Kalathil, Dileep, Shakkottai, Srinivas
Media streaming is the dominant application over wireless edge (access) networks. The increasing softwarization of such networks has led to efforts at intelligent control, wherein application-specific actions may be dynamically taken to enhance the u
Externí odkaz:
http://arxiv.org/abs/2404.07315
Autor:
Mousavi, Sajad, Gutiérrez, Ricardo Luna, Rengarajan, Desik, Gundecha, Vineet, Babu, Ashwin Ramesh, Naug, Avisek, Guillen, Antonio, Sarkar, Soumyendu
Publikováno v:
NeurIPS 2023 Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models 2023(NeurIPS 2023)
We propose a self-correction mechanism for Large Language Models (LLMs) to mitigate issues such as toxicity and fact hallucination. This method involves refining model outputs through an ensemble of critics and the model's own feedback. Drawing inspi
Externí odkaz:
http://arxiv.org/abs/2310.18679
BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models
Autor:
Leong, Wei Qi, Ngui, Jian Gang, Susanto, Yosephine, Rengarajan, Hamsawardhini, Sarveswaran, Kengatharaiyer, Tjhi, William Chandra
The rapid development of Large Language Models (LLMs) and the emergence of novel abilities with scale have necessitated the construction of holistic, diverse and challenging benchmarks such as HELM and BIG-bench. However, at the moment, most of these
Externí odkaz:
http://arxiv.org/abs/2309.06085