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Found 6 papers, 3 papers with code
Kotlin ML Pack: Technical Report
In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises.
Neural Entity Linking: A Survey of Models Based on Deep Learning
This survey presents a comprehensive description of recent neural entity linking (EL) systems developed since 2015 as a result of the "deep learning revolution" in natural language processing.
Tuning Multilingual Transformers for Language-Specific Named Entity Recognition
Our paper addresses the problem of multilingual named entity recognition on the material of 4 languages: Russian, Bulgarian, Czech and Polish.
Multilingual Named Entity Recognition
named-entity-recognition
+3
Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language
This work shows that transfer learning from a multilingual model to monolingual model results in significant growth of performance on such tasks as reading comprehension, paraphrase detection, and sentiment analysis.
Ranked #1 on
Question Answering
on SQuAD1.1
(Hardware Burden metric)
Tuning Multilingual Transformers for Named Entity Recognition on Slavic Languages
Our paper addresses the problem of multilingual named entity recognition on the material of 4 languages: Russian, Bulgarian, Czech and Polish.
Multilingual Named Entity Recognition
named-entity-recognition
+3
DeepPavlov: Open-Source Library for Dialogue Systems
It supports modular as well as end-to-end approaches to implementation of conversational agents.
