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pro vyhledávání: '"Mamou, Jonathan"'
Autor:
Timor, Nadav, Mamou, Jonathan, Korat, Daniel, Berchansky, Moshe, Pereg, Oren, Wasserblat, Moshe, Galanti, Tomer, Gordon, Michal, Harel, David
Accelerating the inference of large language models (LLMs) is an important challenge in artificial intelligence. This paper introduces distributed speculative inference (DSI), a novel distributed inference algorithm that is provably faster than specu
Externí odkaz:
http://arxiv.org/abs/2405.14105
Autor:
Mamou, Jonathan, Pereg, Oren, Korat, Daniel, Berchansky, Moshe, Timor, Nadav, Wasserblat, Moshe, Schwartz, Roy
Speculative decoding is commonly used for reducing the inference latency of large language models. Its effectiveness depends highly on the speculation lookahead (SL)-the number of tokens generated by the draft model at each iteration. In this work we
Externí odkaz:
http://arxiv.org/abs/2405.04304
Adaptive inference is a simple method for reducing inference costs. The method works by maintaining multiple classifiers of different capacities, and allocating resources to each test instance according to its difficulty. In this work, we compare the
Externí odkaz:
http://arxiv.org/abs/2306.02307
The remarkable success of large transformer-based models such as BERT, RoBERTa and XLNet in many NLP tasks comes with a large increase in monetary and environmental cost due to their high computational load and energy consumption. In order to reduce
Externí odkaz:
http://arxiv.org/abs/2204.06271
While vector-based language representations from pretrained language models have set a new standard for many NLP tasks, there is not yet a complete accounting of their inner workings. In particular, it is not entirely clear what aspects of sentence-l
Externí odkaz:
http://arxiv.org/abs/2104.07578
Autor:
Mamou, Jonathan, Le, Hang, Del Rio, Miguel, Stephenson, Cory, Tang, Hanlin, Kim, Yoon, Chung, SueYeon
Deep neural networks (DNNs) have shown much empirical success in solving perceptual tasks across various cognitive modalities. While they are only loosely inspired by the biological brain, recent studies report considerable similarities between repre
Externí odkaz:
http://arxiv.org/abs/2006.01095
Autor:
Roit, Paul, Klein, Ayal, Stepanov, Daniela, Mamou, Jonathan, Michael, Julian, Stanovsky, Gabriel, Zettlemoyer, Luke, Dagan, Ido
Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an attractive open and natural flavour of SRL, potentially attainable from laymen. Recently, a large-scale crowdsourced QA-SRL corpus and a trained parser were released. Trying to
Externí odkaz:
http://arxiv.org/abs/1911.03243
Autor:
Xu, Tongda, Qiu, Ziming, Das, William, Wang, Chuiyu, Langerman, Jack, Nair, Nitin, Aristizabal, Orlando, Mamou, Jonathan, Turnbull, Daniel H., Ketterling, Jeffrey A., Wang, Yao
High-frequency ultrasound (HFU) is well suited for imaging embryonic mice due to its noninvasive and real-time characteristics. However, manual segmentation of the brain ventricles (BVs) and body requires substantial time and expertise. This work pro
Externí odkaz:
http://arxiv.org/abs/1910.09061
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