Search Results for author: Michalis Vlachos

Found 6 papers, 2 papers with code

Large Language Models for Difficulty Estimation of Foreign Language Content with Application to Language Learning

no code implementations10 Sep 2023 Michalis Vlachos, Mircea Lungu, Yash Raj Shrestha, Johannes-Rudolf David

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 language.

An evaluation of quality and robustness of smoothed explanations

no code implementations29 Sep 2021 Ahmad Ajalloeian, Seyed-Mohsen Moosavi-Dezfooli, Michalis Vlachos, Pascal Frossard

However, a combination of additive and non-additive attacks can still manipulate these explanations, which reveals shortcomings in their robustness properties.

Reflective-Net: Learning from Explanations

1 code implementation27 Nov 2020 Johannes Schneider, Michalis Vlachos

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.

Explaining Neural Networks by Decoding Layer Activations

1 code implementation27 May 2020 Johannes Schneider, Michalis Vlachos

We present a `CLAssifier-DECoder' architecture (\emph{ClaDec}) which facilitates the comprehension of the output of an arbitrary layer in a neural network (NN).

General Classification Image Classification

Deceptive AI Explanations: Creation and Detection

no code implementations21 Jan 2020 Johannes Schneider, Christian Meske, Michalis Vlachos

To address this issue, our work investigates how AI models (i. e., deep learning, and existing instruments to increase transparency regarding AI decisions) can be used to create and detect deceptive explanations.

text-classification Text Classification

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