Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Merler, Michele"'
Autor:
Mishra, Mayank, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Prasad, Aditya, Soria, Adriana Meza, Merler, Michele, Selvam, Parameswaran, Surendran, Saptha, Singh, Shivdeep, Sethi, Manish, Dang, Xuan-Hong, Li, Pengyuan, Wu, Kun-Lung, Zawad, Syed, Coleman, Andrew, White, Matthew, Lewis, Mark, Pavuluri, Raju, Koyfman, Yan, Lublinsky, Boris, de Bayser, Maximilien, Abdelaziz, Ibrahim, Basu, Kinjal, Agarwal, Mayank, Zhou, Yi, Johnson, Chris, Goyal, Aanchal, Patel, Hima, Shah, Yousaf, Zerfos, Petros, Ludwig, Heiko, Munawar, Asim, Crouse, Maxwell, Kapanipathi, Pavan, Salaria, Shweta, Calio, Bob, Wen, Sophia, Seelam, Seetharami, Belgodere, Brian, Fonseca, Carlos, Singhee, Amith, Desai, Nirmit, Cox, David D., Puri, Ruchir, Panda, Rameswar
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based age
Externí odkaz:
http://arxiv.org/abs/2405.04324
Large language models have become a vital component in modern NLP, achieving state of the art performance in a variety of tasks. However, they are often inefficient for real-world deployment due to their expensive inference costs. Knowledge distillat
Externí odkaz:
http://arxiv.org/abs/2310.08797
Autor:
Pan, Rangeet, Ibrahimzada, Ali Reza, Krishna, Rahul, Sankar, Divya, Wassi, Lambert Pouguem, Merler, Michele, Sobolev, Boris, Pavuluri, Raju, Sinha, Saurabh, Jabbarvand, Reyhaneh
Code translation aims to convert source code from one programming language (PL) to another. Given the promising abilities of large language models (LLMs) in code synthesis, researchers are exploring their potential to automate code translation. The p
Externí odkaz:
http://arxiv.org/abs/2308.03109
Autor:
Yuan, Jiaqing, Merler, Michele, Choudhury, Mihir, Pavuluri, Raju, Singh, Munindar P., Vukovic, Maja
Entity standardization maps noisy mentions from free-form text to standard entities in a knowledge base. The unique challenge of this task relative to other entity-related tasks is the lack of surrounding context and numerous variations in the surfac
Externí odkaz:
http://arxiv.org/abs/2306.03316
Autor:
Trivedi, Aashka, Udagawa, Takuma, Merler, Michele, Panda, Rameswar, El-Kurdi, Yousef, Bhattacharjee, Bishwaranjan
Large pretrained language models have achieved state-of-the-art results on a variety of downstream tasks. Knowledge Distillation (KD) into a smaller student model addresses their inefficiency, allowing for deployment in resource-constrained environme
Externí odkaz:
http://arxiv.org/abs/2303.09639
Autor:
Finkler, Ulrich, Merler, Michele, Panda, Rameswar, Jaiswal, Mayoore S., Wu, Hui, Ramakrishnan, Kandan, Chen, Chun-Fu, Cho, Minsik, Kung, David, Feris, Rogerio, Bhattacharjee, Bishwaranjan
Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification. Due to the significant computational burden of the search phase, most NAS methods have focused so far on
Externí odkaz:
http://arxiv.org/abs/2011.10608
Autor:
Panda, Rameswar, Merler, Michele, Jaiswal, Mayoore, Wu, Hui, Ramakrishnan, Kandan, Finkler, Ulrich, Chen, Chun-Fu, Cho, Minsik, Kung, David, Feris, Rogerio, Bhattacharjee, Bishwaranjan
Neural Architecture Search (NAS) is an open and challenging problem in machine learning. While NAS offers great promise, the prohibitive computational demand of most of the existing NAS methods makes it difficult to directly search the architectures
Externí odkaz:
http://arxiv.org/abs/2006.13314
Autor:
Merler, Michele, Santos, Cicero Nogueira dos, Martino, Mauro, Gliozzo, Alfio M., Smith, John R.
We introduce a multi-modal discriminative and generative frame-work capable of assisting humans in producing visual content re-lated to a given theme, starting from a collection of documents(textual, visual, or both). This framework can be used by ed
Externí odkaz:
http://arxiv.org/abs/2002.02369
Face recognition is a long standing challenge in the field of Artificial Intelligence (AI). The goal is to create systems that accurately detect, recognize, verify, and understand human faces. There are significant technical hurdles in making these s
Externí odkaz:
http://arxiv.org/abs/1901.10436
Autor:
Merler, Michele, Joshi, Dhiraj, Nguyen, Quoc-Bao, Hammer, Stephen, Kent, John, Smith, John R., Feris, Rogerio S.
The production of sports highlight packages summarizing a game's most exciting moments is an essential task for broadcast media. Yet, it requires labor-intensive video editing. We propose a novel approach for auto-curating sports highlights, and use
Externí odkaz:
http://arxiv.org/abs/1707.07075