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Found 11 papers, 2 papers with code
LIORI at the FinCausal 2020 Shared task
In this paper, we describe the results of team LIORI at the FinCausal 2020 Shared task held as a part of the 1st Joint Workshop on Financial Narrative Processing and MultiLingual Financial Summarisation.
LIORI at SemEval-2021 Task 2: Span Prediction and Binary Classification approaches to Word-in-Context Disambiguation
This paper presents our approaches to SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation task.
LIORI at SemEval-2021 Task 8: Ask Transformer for measurements
This work describes our approach for subtasks of SemEval-2021 Task 8: MeasEval: Counts and Measurements which took the official first place in the competition.
Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction
This paper describes our approach to {``}DeftEval: Extracting Definitions from Free Text in Textbooks{''} competition held as a part of Semeval 2020.
Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media
This paper describes our approach to emphasis selection for written text in visual media as a solution for SemEval 2020 Task 10.
BERT of all trades, master of some
This paper describes our results for TRAC 2020 competition held together with the conference LREC 2020.
Ranked #1 on
Text Classification
on TRAC2-Benghali. Task 2.
Unsupervised cross-lingual matching of product classifications
Unsupervised cross-lingual embeddings mapping has provided a unique tool for completely unsupervised translation even for languages with different scripts.
Automatic verbal aggression detection for Russian and American imageboards
The problem of aggression for Internet communities is rampant.
Detecting state of aggression in sentences using CNN
In this article we study verbal expression of aggression and its detection using machine learning and neural networks methods.
Determination of the Internet Anonymity Influence on the Level of Aggression and Usage of Obscene Lexis
It was established that Russian obscene lexis was used to express the emotional state of aggression only in 60. 4% of cases for 2ch. hk.
