Zobrazeno 1 - 10
of 85 693
pro vyhledávání: '"KRISHNA A P"'
Autor:
Krishna, Satyapriya, Krishna, Kalpesh, Mohananey, Anhad, Schwarcz, Steven, Stambler, Adam, Upadhyay, Shyam, Faruqui, Manaal
Large Language Models (LLMs) have demonstrated significant performance improvements across various cognitive tasks. An emerging application is using LLMs to enhance retrieval-augmented generation (RAG) capabilities. These systems require LLMs to unde
Externí odkaz:
http://arxiv.org/abs/2409.12941
Modern deep learning continues to achieve outstanding performance on an astounding variety of high-dimensional tasks. In practice, this is obtained by fitting deep neural models to all the input data with minimal feature engineering, thus sacrificing
Externí odkaz:
http://arxiv.org/abs/2408.10693
Autor:
Li, Baiqi, Lin, Zhiqiu, Peng, Wenxuan, Nyandwi, Jean de Dieu, Jiang, Daniel, Ma, Zixian, Khanuja, Simran, Krishna, Ranjay, Neubig, Graham, Ramanan, Deva
Vision-language models (VLMs) have made significant progress in recent visual-question-answering (VQA) benchmarks that evaluate complex visio-linguistic reasoning. However, are these models truly effective? In this work, we show that VLMs still strug
Externí odkaz:
http://arxiv.org/abs/2410.14669
Autor:
Pathre, Pranjali, Gupta, Gunjan, Qureshi, M. Nomaan, Brunda, Mandyam, Brahmbhatt, Samarth, Krishna, K. Madhava
Visual servoing, the method of controlling robot motion through feedback from visual sensors, has seen significant advancements with the integration of optical flow-based methods. However, its application remains limited by inherent challenges, such
Externí odkaz:
http://arxiv.org/abs/2410.12432
Autor:
Krishna, Rahul, Pan, Rangeet, Pavuluri, Raju, Tamilselvam, Srikanth, Vukovic, Maja, Sinha, Saurabh
Large Language Models for Code (or code LLMs) are increasingly gaining popularity and capabilities, offering a wide array of functionalities such as code completion, code generation, code summarization, test generation, code translation, and more. To
Externí odkaz:
http://arxiv.org/abs/2410.13007
Autor:
Gorti, Satya Krishna, Gofman, Ilan, Liu, Zhaoyan, Wu, Jiapeng, Vouitsis, Noël, Yu, Guangwei, Cresswell, Jesse C., Hosseinzadeh, Rasa
Text-to-SQL generation enables non-experts to interact with databases via natural language. Recent advances rely on large closed-source models like GPT-4 that present challenges in accessibility, privacy, and latency. To address these issues, we focu
Externí odkaz:
http://arxiv.org/abs/2410.12916
Autor:
Bobba, Kumar Srinivas, K, Kartheeban, Sai, Vamsi Krishna, Bugga, Dinesh, Bolla, Vijaya Mani Surendra
This project proposes the development of a comprehensive real-time biodiversity monitoring system that harnesses sound data through a network of acoustic sensors and advanced artificial intelligence algorithms. The system analyzes sound recordings fr
Externí odkaz:
http://arxiv.org/abs/2410.12897
Large language models (LLMs) trained with Reinforcement Learning from Human Feedback (RLHF) have demonstrated remarkable capabilities, but their underlying reward functions and decision-making processes remain opaque. This paper introduces a novel ap
Externí odkaz:
http://arxiv.org/abs/2410.12491
In this article, we employ physics-informed residual learning (PIRL) and propose a pricing method for European options under a regime-switching framework, where closed-form solutions are not available. We demonstrate that the proposed approach serves
Externí odkaz:
http://arxiv.org/abs/2410.10474
Autor:
Gupta, Naman, Kirtania, Shashank, Gupta, Priyanshu, Kariya, Krishna, Gulwani, Sumit, Iyer, Arun, Parthasarathy, Suresh, Radhakrishna, Arjun, Rajamani, Sriram K., Soares, Gustavo
Large Language Models (LLMs) often generate incorrect or outdated information, especially in low-resource settings or when dealing with private data. To address this, Retrieval-Augmented Generation (RAG) uses external knowledge bases (KBs), but these
Externí odkaz:
http://arxiv.org/abs/2410.10584