Results 241 to 250 of about 13,934,700 (305)

Deconstructing the text: Performance implications

Literature in Performance, 1983
Jill Taft‐Kaufman
openaire   +2 more sources

I. Text-Performance

1999
Paul J. Perron
openaire   +2 more sources

The Theatre of Garcia Lorca: Text, Performance, Psychoanalysis

Hispanic Review, 2001
C. Christopher Soufas, Paul Julian Smith
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Mutual Interferences of Driving and Texting Performance

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2014
Despite legislative and social campaigns to reduce texting while driving, drivers continue to text behind the wheel. There is abundant evidence demonstrating that texting while driving impairs driving performance. While past driver distraction research has focused on how texting influences driving, the influence of driving on texting behaviors is ...
Jibo He, Alex Chaparro, Joseph Crandall, Colton Turner, Kirsten Turner, Jake Ellis   +5 more
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Movement, Text, Performance

This Element argues that movement, overseen by a movement director, is vital for theatre-making. It can support actors with characterisation and playing others responsibly and ethically, for scripted and non-scripted tasks: from dances to fights, from ...
Paul Allain
semanticscholar   +1 more source

Improving Text Embeddings with Large Language Models

Annual Meeting of the Association for Computational Linguistics, 2023
In this paper, we introduce a novel and simple method for obtaining high-quality text embeddings using only synthetic data and less than 1k training steps.
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei   +5 more
semanticscholar   +1 more source

Mutual interferences of driving and texting performance

Computers in Human Behavior, 2015
Concurrent texting entry impairs driving performance.Driving causes more errors of text messages and reduces key entry speed.Regression model based texting behaviors can reliably detect texting while driving. Despite legislative and social campaigns to reduce texting while driving, drivers continue to text behind the wheel.
He, Jibo, Chaparro, Alex, Wu, Xiaohui, Crandall, Joseph, Ellis, Jake   +4 more
openaire   +2 more sources

The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Neural Information Processing Systems
The performance of a large language model (LLM) depends heavily on the quality and size of its pretraining dataset. However, the pretraining datasets for state-of-the-art open LLMs like Llama 3 and Mixtral are not publicly available and very little is ...
Guilherme Penedo, Hynek Kydlícek, Loubna Ben Allal, Anton Lozhkov, Margaret Mitchell, Colin Raffel, L. V. Werra, Thomas Wolf   +7 more
semanticscholar   +1 more source

LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

arXiv.org
Large decoder-only language models (LLMs) are the state-of-the-art models on most of today's NLP tasks and benchmarks. Yet, the community is only slowly adopting these models for text embedding tasks, which require rich contextualized representations. In
Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, Dzmitry Bahdanau, Nicolas Chapados, Siva Reddy   +5 more
semanticscholar   +1 more source

InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model

arXiv.org
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form text-image composition and comprehension. This model goes beyond conventional vision-language understanding, adeptly crafting interleaved text-image content ...
Xiao-wen Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Bin Wang, Linke Ouyang, Xilin Wei, Songyang Zhang, Haodong Duan, Maosong Cao, Wenwei Zhang, Yining Li, Hang Yan, Yang Gao, Xinyue Zhang, Wei Li, Jingwen Li, Kai Chen, Conghui He, Xingcheng Zhang, Yu Qiao, Dahua Lin, Jiaqi Wang   +22 more
semanticscholar   +1 more source