Locked History Actions

Diff for "seminar"

Differences between revisions 419 and 420
Revision 419 as of 2021-09-09 12:12:51
Size: 6287
Comment:
Revision 420 as of 2021-09-09 12:52:21
Size: 6363
Comment:
Deletions are marked like this. Additions are marked like this.
Line 24: Line 24:
||<style="border:0;padding-left:30px;padding-bottom:5px">'''Talk title will be available shortly''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}|| ||<style="border:0;padding-left:30px;padding-bottom:5px">'''When classification accuracy is not enough: Explaining news credibility assessment and measuring users' reaction''' &#160;{{attachment:seminarium-archiwum/icon-pl.gif|Talk delivered in Polish.}}||

Natural Language Processing Seminar 2021–2022

The NLP Seminar is organised by the Linguistic Engineering Group at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS). It takes place on (some) Mondays, usually at 10:15 am, currently online – please use the link next to the presentation title. All recorded talks are available on YouTube.

seminarium

4 October 2021

Joanna Byszuk (Institute of Polish Language, Polish Academy of Sciences)

Talk title will be available shortly  Talk delivered in Polish.

Talk summary will be available shortly.

18 October 2021

Jan Kocoń, Przemysław Kazienko (Wrocław University of Technology)

Personalized NLP  Talk delivered in Polish.

Many natural language processing tasks, such as classifying offensive, toxic, or emotional texts, are inherently subjective in nature. This is a major challenge, especially with regard to the annotation process. Humans tend to perceive textual content in their own individual way. Most current annotation procedures aim to achieve a high level of agreement in order to generate a high quality reference source. Existing machine learning methods commonly rely on agreed output values that are the same for all annotators. However, annotation guidelines for subjective content can limit annotators' decision-making freedom. Motivated by moderate annotation agreement on offensive and emotional content datasets, we hypothesize that a personalized approach should be introduced for such subjective tasks. We propose new deep learning architectures that take into account not only the content but also the characteristics of the individual. We propose different approaches for learning the representation and processing of data about text readers. Experiments were conducted on four datasets: Wikipedia discussion texts labeled with attack, aggression, and toxicity, and opinions annotated with ten numerical emotional categories. All of our models based on human biases and their representations significantly improve prediction quality in subjective tasks evaluated from an individual's perspective. Additionally, we have developed requirements for annotation, personalization, and content processing procedures to make our solutions human-centric.

8 November 2021

Ryszard Tuora, Łukasz Kobyliński (Institute of Computer Science, Polish Academy of Sciences)

Dependency Trees in Automatic Inflection of Multi Word Expressions in Polish  Talk delivered in Polish.

Talk summary will be available shortly.

22 November 2021

Piotr Przybyła (Institute of Computer Science, Polish Academy of Sciences)

When classification accuracy is not enough: Explaining news credibility assessment and measuring users' reaction  Talk delivered in Polish.

Talk summary will be available shortly.

Please see also the talks given in 2000–2015 and 2015–2020.