Zobrazeno 1 - 10
of 2 103
pro vyhledávání: '"P. Shashidhar"'
Autor:
Kumar, Sahil, Paikar, Deepa, Vutukuri, Kiran Sai, Ali, Haider, Ainala, Shashidhar Reddy, Krishnan, Aditya Murli, Zhang, Youshan
Effective communication within universities is crucial for addressing the diverse information needs of students, alumni, and external stakeholders. However, existing chatbot systems often fail to deliver accurate, context-specific responses, resultin
Externí odkaz:
http://arxiv.org/abs/2410.16385
Large language models demonstrate impressive reasoning abilities but struggle to provide personalized content due to their lack of individual user preference information. Existing methods, such as in-context learning and parameter-efficient fine-tuni
Externí odkaz:
http://arxiv.org/abs/2410.03731
Autor:
Javaji, Shashidhar Reddy, Zhu, Zining
Large language models (LLMs) can store a massive amount of knowledge, yet their potential to acquire new knowledge remains unknown. We propose a novel evaluation framework that evaluates this capability. This framework prompts LLMs to generate questi
Externí odkaz:
http://arxiv.org/abs/2409.17172
Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these problems, i.e.,
Externí odkaz:
http://arxiv.org/abs/2405.06800
Video captioning in Nepali, a language written in the Devanagari script, presents a unique challenge due to the lack of existing academic work in this domain. This work develops a novel encoder-decoder paradigm for Nepali video captioning to tackle t
Externí odkaz:
http://arxiv.org/abs/2312.07418
Democratizing LLMs: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models
The dominance of proprietary LLMs has led to restricted access and raised information privacy concerns. High-performing open-source alternatives are crucial for information-sensitive and high-volume applications but often lag behind in performance. T
Externí odkaz:
http://arxiv.org/abs/2310.07611
This research focuses on utilizing natural language processing techniques to predict stock price fluctuations, with a specific interest in early detection of economic, political, social, and technological changes that can be leveraged for capturing m
Externí odkaz:
http://arxiv.org/abs/2310.04880
Recommender systems have emerged as a crucial component of the modern web ecosystem. The effectiveness and accuracy of such systems are critical for providing users with personalized recommendations that meet their specific interests and needs. In th
Externí odkaz:
http://arxiv.org/abs/2310.04878
Publikováno v:
Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 3, Pp 501-507 (2024)
Mineral identification plays a vital role in understanding the diversity and past habitability of the Martian surface. Mineral mapping by the traditional manual method is time-consuming and the unavailability of ground truth data limited the research
Externí odkaz:
https://doaj.org/article/35c7132616be45068cc1aab37c5c0718
In this paper, we propose a hybrid model combining genetic algorithm and hill climbing algorithm for optimizing Convolutional Neural Networks (CNNs) on the CIFAR-100 dataset. The proposed model utilizes a population of chromosomes that represent the
Externí odkaz:
http://arxiv.org/abs/2308.13099