Zobrazeno 1 - 10
of 416
pro vyhledávání: '"Kumar, Dhruv"'
Autor:
Arora, Chaitanya, Venaik, Utkarsh, Singh, Pavit, Goyal, Sahil, Tyagi, Jatin, Goel, Shyama, Singhal, Ujjwal, Kumar, Dhruv
This paper investigates the usage patterns of undergraduate and graduate students when engaging with large language models (LLMs) to tackle programming assignments in the context of advanced computing courses. Existing work predominantly focuses on t
Externí odkaz:
http://arxiv.org/abs/2404.04603
We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance. mEdIT models are trained by fine-tuning multi-lingual large, pre-trained language models (LLMs) via instruction tuning.
Externí odkaz:
http://arxiv.org/abs/2402.16472
As the text generation capabilities of large language models become increasingly prominent, recent studies have focused on controlling particular aspects of the generated text to make it more personalized. However, most research on controllable text
Externí odkaz:
http://arxiv.org/abs/2402.04914
This study investigates the integration and impact of Large Language Models (LLMs), like ChatGPT, in India's healthcare sector. Our research employs a dual approach, engaging both general users and medical professionals through surveys and interviews
Externí odkaz:
http://arxiv.org/abs/2401.15605
Autor:
Mhasakar, Manas, Sharma, Shikhar, Mehra, Apurv, Venaik, Utkarsh, Singhal, Ujjwal, Kumar, Dhruv, Mittal, Kashish
In this paper, we investigate the potential of Large Language Models (LLMs) to improve English speaking skills. This is particularly relevant in countries like India, where English is crucial for academic, professional, and personal communication but
Externí odkaz:
http://arxiv.org/abs/2401.15595
Conventional class feedback systems often fall short, relying on static, unengaging surveys offering little incentive for student participation. To address this, we present OpineBot, a novel system employing large language models (LLMs) to conduct pe
Externí odkaz:
http://arxiv.org/abs/2401.15589
This study evaluates the effectiveness of various large language models (LLMs) in performing tasks common among undergraduate computer science students. Although a number of research studies in the computing education community have explored the poss
Externí odkaz:
http://arxiv.org/abs/2402.01687
The emergence of digital payment systems has transformed how individuals conduct financial transactions, offering convenience, security, and efficiency. One groundbreaking innovation making waves in the Indian financial landscape is the Unified Payme
Externí odkaz:
http://arxiv.org/abs/2401.09937
Generating unit tests is a crucial task in software development, demanding substantial time and effort from programmers. The advent of Large Language Models (LLMs) introduces a novel avenue for unit test script generation. This research aims to exper
Externí odkaz:
http://arxiv.org/abs/2312.10622
Autor:
Dvivedi, Shubhang Shekhar, Vijay, Vyshnav, Pujari, Sai Leela Rahul, Lodh, Shoumik, Kumar, Dhruv
This paper presents a comprehensive comparative analysis of Large Language Models (LLMs) for generation of code documentation. Code documentation is an essential part of the software writing process. The paper evaluates models such as GPT-3.5, GPT-4,
Externí odkaz:
http://arxiv.org/abs/2312.10349