Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Vlachos, Michalis"'
We leverage generative large language models for language learning applications, focusing on estimating the difficulty of foreign language texts and simplifying them to lower difficulty levels. We frame both tasks as prediction problems and develop a
Externí odkaz:
http://arxiv.org/abs/2407.18061
We use large language models to aid learners enhance proficiency in a foreign language. This is accomplished by identifying content on topics that the user is interested in, and that closely align with the learner's proficiency level in that foreign
Externí odkaz:
http://arxiv.org/abs/2309.05142
Autor:
Schneider, Johannes, Vlachos, Michalis
Deep learning has made tremendous progress in the last decade. A key success factor is the large amount of architectures, layers, objectives, and optimization techniques. They include a myriad of variants related to attention, normalization, skip con
Externí odkaz:
http://arxiv.org/abs/2302.00722
Publikováno v:
In The Leadership Quarterly December 2024 35(6)
Autor:
Schneider, Johannes, Vlachos, Michalis
Publikováno v:
Data Mining and Knowledge Discovery, 1-22, 2023
Humans possess a remarkable capability to make fast, intuitive decisions, but also to self-reflect, i.e., to explain to oneself, and to efficiently learn from explanations by others. This work provides the first steps toward mimicking this process by
Externí odkaz:
http://arxiv.org/abs/2011.13986
Autor:
Mesnage, Cédric, Vlachos, Michalis
Global warming is a major environmental concern of our times. It has been suggested that the planting of trees could constitute a way of mitigating the adverse effects of the increasing anthropogenic carbon emissions. We developed a simple data-drive
Externí odkaz:
http://arxiv.org/abs/2007.00508
Autor:
Schneider, Johannes, Vlachos, Michalis
Publikováno v:
Intelligent Data Analysis (IDA), 2021
We present a `CLAssifier-DECoder' architecture (\emph{ClaDec}) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN). It uses a decoder to transform the non-interpretable representation of the given layer to
Externí odkaz:
http://arxiv.org/abs/2005.13630
Publikováno v:
International Conference on Agents and Artificial Intelligence (2022)
Artificial intelligence (AI) comes with great opportunities but can also pose significant risks. Automatically generated explanations for decisions can increase transparency and foster trust, especially for systems based on automated predictions by A
Externí odkaz:
http://arxiv.org/abs/2001.07641
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