Zobrazeno 1 - 10
of 247
pro vyhledávání: '"P Murahari"'
Autor:
Samuel, Vinay, Zou, Henry Peng, Zhou, Yue, Chaudhari, Shreyas, Kalyan, Ashwin, Rajpurohit, Tanmay, Deshpande, Ameet, Narasimhan, Karthik, Murahari, Vishvak
Persona agents, which are LLM agents that act according to an assigned persona, have demonstrated impressive contextual response capabilities across various applications. These persona agents offer significant enhancements across diverse sectors, suc
Externí odkaz:
http://arxiv.org/abs/2407.18416
Autor:
Chaudhari, Shreyas, Aggarwal, Pranjal, Murahari, Vishvak, Rajpurohit, Tanmay, Kalyan, Ashwin, Narasimhan, Karthik, Deshpande, Ameet, da Silva, Bruno Castro
State-of-the-art large language models (LLMs) have become indispensable tools for various tasks. However, training LLMs to serve as effective assistants for humans requires careful consideration. A promising approach is reinforcement learning from hu
Externí odkaz:
http://arxiv.org/abs/2404.08555
Autor:
Himanshu Prasad, P V Satyanarayana Murthy, P Murahari, L.M.V Kumar, G.P.V Subbaiah, C Chandrashekhar, Mahendra Kumar
Publikováno v:
Journal of Clinical and Scientific Research, Vol 6, Iss 2, Pp 117-120 (2017)
Spinal epidural abscess (SEA) is a rare but potentially devastating condition. Tuberculosis (TB) as the aetiology of epidural abscess especially without bony the involvement of vertebrae is uncommon. We present here, our experience with two cases whe
Externí odkaz:
https://doaj.org/article/ba5b256811864dc293ac8d8d878b4180
Autor:
Aggarwal, Pranjal, Murahari, Vishvak, Rajpurohit, Tanmay, Kalyan, Ashwin, Narasimhan, Karthik, Deshpande, Ameet
The advent of large language models (LLMs) has ushered in a new paradigm of search engines that use generative models to gather and summarize information to answer user queries. This emerging technology, which we formalize under the unified framework
Externí odkaz:
http://arxiv.org/abs/2311.09735
Autor:
Murahari, Vishvak, Deshpande, Ameet, Clark, Peter, Rajpurohit, Tanmay, Sabharwal, Ashish, Narasimhan, Karthik, Kalyan, Ashwin
Quantitative evaluation metrics have traditionally been pivotal in gauging the advancements of artificial intelligence systems, including large language models (LLMs). However, these metrics have inherent limitations. Given the intricate nature of re
Externí odkaz:
http://arxiv.org/abs/2311.02807
As language models increase in size by the day, methods for efficient inference are critical to leveraging their capabilities for various applications. Prior work has investigated techniques like model pruning, knowledge distillation, and data multip
Externí odkaz:
http://arxiv.org/abs/2305.14706
Autor:
Deshpande, Ameet, Jimenez, Carlos E., Chen, Howard, Murahari, Vishvak, Graf, Victoria, Rajpurohit, Tanmay, Kalyan, Ashwin, Chen, Danqi, Narasimhan, Karthik
Semantic textual similarity (STS), a cornerstone task in NLP, measures the degree of similarity between a pair of sentences, and has broad application in fields such as information retrieval and natural language understanding. However, sentence simil
Externí odkaz:
http://arxiv.org/abs/2305.15093
Large language models (LLMs) have shown incredible capabilities and transcended the natural language processing (NLP) community, with adoption throughout many services like healthcare, therapy, education, and customer service. Since users include peo
Externí odkaz:
http://arxiv.org/abs/2304.05335
Publikováno v:
Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-17 (2024)
Abstract Visual examination of the surface topography, in conjunction with the other sensors, may confirm the existence of chatter. Online chatter detection during real machining operations is possible with the use of sensors, and the presence of noi
Externí odkaz:
https://doaj.org/article/fe52a288d85f4526ae9e46b91905e2b5
Autor:
Murahari, Vishvak, Deshpande, Ameet, Jimenez, Carlos E., Shafran, Izhak, Wang, Mingqiu, Cao, Yuan, Narasimhan, Karthik
The widespread adoption of large language models such as ChatGPT and Bard has led to unprecedented demand for these technologies. The burgeoning cost of inference for ever-increasing model sizes coupled with hardware shortages has limited affordable
Externí odkaz:
http://arxiv.org/abs/2302.12441