Zobrazeno 1 - 10
of 2 488
pro vyhledávání: '"A Pratyusha"'
Fine-tuning is a crucial paradigm for adapting pre-trained large language models to downstream tasks. Recently, methods like Low-Rank Adaptation (LoRA) have been shown to match the performance of fully fine-tuned models on various tasks with an extre
Externí odkaz:
http://arxiv.org/abs/2410.21228
Study of correlation functions in AdS/CFT and in-in correlators in de Sitter space often requires the computation of Witten diagrams. Due to the complexity of evaluating radial integrals for these correlators, several indirect approaches have been de
Externí odkaz:
http://arxiv.org/abs/2408.00074
Autor:
Maiti, Pratyusha, Goel, Ashok K.
Jill Watson, a virtual teaching assistant powered by LLMs, answers student questions and engages them in extended conversations on courseware provided by the instructors. In this paper, we analyze student interactions with Jill across multiple course
Externí odkaz:
http://arxiv.org/abs/2407.17429
Publikováno v:
Indian Journal of Neonatal Medicine and Research, Vol 8, Iss 4, Pp 01-10 (2020)
Introduction: Neonatal sepsis is responsible for 30% to 50% of all neonatal deaths in developing countries in a year. Incidence of neonatal sepsis was reported to range between 30.7-35.9 per 1000 live births in low middle income African and Southeast
Externí odkaz:
https://doaj.org/article/ad2dcb868950426fa971faee3cb1f7ba
In this work, we consider data association problems involving multi-object tracking (MOT). In particular, we address the challenges arising from object occlusions. We propose a framework called approximate dynamic programming track (ADPTrack), which
Externí odkaz:
http://arxiv.org/abs/2405.15137
Autor:
Taneja, Karan, Maiti, Pratyusha, Kakar, Sandeep, Guruprasad, Pranav, Rao, Sanjeev, Goel, Ashok K.
Conversational AI agents often require extensive datasets for training that are not publicly released, are limited to social chit-chat or handling a specific domain, and may not be easily extended to accommodate the latest advances in AI technologies
Externí odkaz:
http://arxiv.org/abs/2405.11070
Autor:
Bhalerao, Omkar, Suckow, Stephan, Windgassen, Horst, Biller, Harry, Fotiadis, Konstantinos, Simos, Stelios, Chatzianagnostou, Evangelia, Spasopoulos, Dimosthenis, Das, Pratyusha, Markey, Laurent, Weeber, Jean-Claude, Pleros, Nikos, Schirmer, Matthias, Lemme, Max C.
Plasmonic refractive index sensors are essential for detecting subtle variations in the ambient environment through surface plasmon interactions. Current efforts utilizing CMOS-compatible, plasmo-photonic Mach-Zehnder interferometers with active powe
Externí odkaz:
http://arxiv.org/abs/2405.05716
Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions. Yet these language models are known to perpetuate systematic racial prejudices, making their judgments bi
Externí odkaz:
http://arxiv.org/abs/2403.00742
Autor:
Fu, Haotian, Sharma, Pratyusha, Stengel-Eskin, Elias, Konidaris, George, Roux, Nicolas Le, Côté, Marc-Alexandre, Yuan, Xingdi
We present an algorithm for skill discovery from expert demonstrations. The algorithm first utilizes Large Language Models (LLMs) to propose an initial segmentation of the trajectories. Following that, a hierarchical variational inference framework i
Externí odkaz:
http://arxiv.org/abs/2402.16354
Autor:
Sharma, Pratyusha, Shaham, Tamar Rott, Baradad, Manel, Fu, Stephanie, Rodriguez-Munoz, Adrian, Duggal, Shivam, Isola, Phillip, Torralba, Antonio
What does learning to model relationships between strings teach large language models (LLMs) about the visual world? We systematically evaluate LLMs' abilities to generate and recognize an assortment of visual concepts of increasing complexity and th
Externí odkaz:
http://arxiv.org/abs/2401.01862