Zobrazeno 1 - 10
of 12 721
pro vyhledávání: '"Sreedhar AS"'
We generate Gaussian radial function based higher order compact RBF-FD formulas for some differential operators. Analytical expressions for weights associated to first and second derivative formulas (up to order 10) and 2D-Laplacian formulas (up to o
Externí odkaz:
http://arxiv.org/abs/2412.10036
The growing adoption of machine learning (ML) in modelling atmospheric and oceanic processes offers a promising alternative to traditional numerical methods. It is essential to benchmark the performance of both ML and physics-informed ML (PINN) model
Externí odkaz:
http://arxiv.org/abs/2411.19031
Autor:
Ma, Jenny, Sreedhar, Karthik, Liu, Vivian, Wang, Sitong, Perez, Pedro Alejandro, Sahni, Riya, Chilton, Lydia B.
Recent advancements in large language models have significantly expedited the process of generating front-end code. This allows users to rapidly prototype user interfaces and ideate through code, a process known as exploratory programming. However, e
Externí odkaz:
http://arxiv.org/abs/2410.00400
Autor:
Hammam, Ahmed, Sreedhar, Bharathwaj Krishnaswami, Kawa, Nura, Patzelt, Tim, De Candido, Oliver
Advancing Machine Learning (ML)-based perception models for autonomous systems necessitates addressing weak spots within the models, particularly in challenging Operational Design Domains (ODDs). These are environmental operating conditions of an aut
Externí odkaz:
http://arxiv.org/abs/2408.17311
Autor:
Ma, Jenny, Sreedhar, Karthik, Liu, Vivian, Wang, Sitong, Perez, Pedro Alejandro, Chilton, Lydia B.
Large language models (LLMs) are remarkably good at writing code. A particularly valuable case of human-LLM collaboration is code-based UI prototyping, a method for creating interactive prototypes that allows users to view and fully engage with a use
Externí odkaz:
http://arxiv.org/abs/2407.08474
Autor:
Abdelaziz, Ibrahim, Basu, Kinjal, Agarwal, Mayank, Kumaravel, Sadhana, Stallone, Matthew, Panda, Rameswar, Rizk, Yara, Bhargav, GP, Crouse, Maxwell, Gunasekara, Chulaka, Ikbal, Shajith, Joshi, Sachin, Karanam, Hima, Kumar, Vineet, Munawar, Asim, Neelam, Sumit, Raghu, Dinesh, Sharma, Udit, Soria, Adriana Meza, Sreedhar, Dheeraj, Venkateswaran, Praveen, Unuvar, Merve, Cox, David, Roukos, Salim, Lastras, Luis, Kapanipathi, Pavan
Large language models (LLMs) have recently shown tremendous promise in serving as the backbone to agentic systems, as demonstrated by their performance in multi-faceted, challenging benchmarks like SWE-Bench and Agent-Bench. However, to realize the t
Externí odkaz:
http://arxiv.org/abs/2407.00121
Dialogue policies play a crucial role in developing task-oriented dialogue systems, yet their development and maintenance are challenging and typically require substantial effort from experts in dialogue modeling. While in many situations, large amou
Externí odkaz:
http://arxiv.org/abs/2406.15214
Autor:
Nvidia, Adler, Bo, Agarwal, Niket, Aithal, Ashwath, Anh, Dong H., Bhattacharya, Pallab, Brundyn, Annika, Casper, Jared, Catanzaro, Bryan, Clay, Sharon, Cohen, Jonathan, Das, Sirshak, Dattagupta, Ayush, Delalleau, Olivier, Derczynski, Leon, Dong, Yi, Egert, Daniel, Evans, Ellie, Ficek, Aleksander, Fridman, Denys, Ghosh, Shaona, Ginsburg, Boris, Gitman, Igor, Grzegorzek, Tomasz, Hero, Robert, Huang, Jining, Jawa, Vibhu, Jennings, Joseph, Jhunjhunwala, Aastha, Kamalu, John, Khan, Sadaf, Kuchaiev, Oleksii, LeGresley, Patrick, Li, Hui, Liu, Jiwei, Liu, Zihan, Long, Eileen, Mahabaleshwarkar, Ameya Sunil, Majumdar, Somshubra, Maki, James, Martinez, Miguel, de Melo, Maer Rodrigues, Moshkov, Ivan, Narayanan, Deepak, Narenthiran, Sean, Navarro, Jesus, Nguyen, Phong, Nitski, Osvald, Noroozi, Vahid, Nutheti, Guruprasad, Parisien, Christopher, Parmar, Jupinder, Patwary, Mostofa, Pawelec, Krzysztof, Ping, Wei, Prabhumoye, Shrimai, Roy, Rajarshi, Saar, Trisha, Sabavat, Vasanth Rao Naik, Satheesh, Sanjeev, Scowcroft, Jane Polak, Sewall, Jason, Shamis, Pavel, Shen, Gerald, Shoeybi, Mohammad, Sizer, Dave, Smelyanskiy, Misha, Soares, Felipe, Sreedhar, Makesh Narsimhan, Su, Dan, Subramanian, Sandeep, Sun, Shengyang, Toshniwal, Shubham, Wang, Hao, Wang, Zhilin, You, Jiaxuan, Zeng, Jiaqi, Zhang, Jimmy, Zhang, Jing, Zhang, Vivienne, Zhang, Yian, Zhu, Chen
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distri
Externí odkaz:
http://arxiv.org/abs/2406.11704
Autor:
Bhargav, G P Shrivatsa, Neelam, Sumit, Sharma, Udit, Ikbal, Shajith, Sreedhar, Dheeraj, Karanam, Hima, Joshi, Sachindra, Dhoolia, Pankaj, Garg, Dinesh, Croutwater, Kyle, Qi, Haode, Wayne, Eric, Murdock, J William
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety of industry-grade applications. Key requirements of this system include
Externí odkaz:
http://arxiv.org/abs/2406.08848
Autor:
Wang, Zhilin, Dong, Yi, Delalleau, Olivier, Zeng, Jiaqi, Shen, Gerald, Egert, Daniel, Zhang, Jimmy J., Sreedhar, Makesh Narsimhan, Kuchaiev, Oleksii
High-quality preference datasets are essential for training reward models that can effectively guide large language models (LLMs) in generating high-quality responses aligned with human preferences. As LLMs become stronger and better aligned, permiss
Externí odkaz:
http://arxiv.org/abs/2406.08673