Papers by Michal Mochtak

1 papers
The ParlaSent Multilingual Training Dataset for Sentiment Identification in Parliamentary Proceedings (2024.lrec-main)

Copied to clipboard

Challenge: The paper presents a new training dataset of sentences in 7 languages, manually annotated for sentiment, which is used in a series of experiments focused on training a robust sentiment identifier for parliamentary proceedings.
Approach: They propose to use a dataset of sentences manually annotated for sentiment to train a robust sentiment identifier for parliamentary proceedings.
Outcome: The proposed model performs very well on languages not seen during fine-tuning and additional fine- tuning data from other languages significantly improves the target parliament’s results.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations