Papers by Robert Mroczkowski
Going beyond research datasets: Novel intent discovery in the industry setting (2023.findings-eacl)
Copied to clipboard
| Challenge: | Novel intent discovery automates grouping of similar messages to identify previously unknown intents. |
| Approach: | They propose to use question-only data to improve the intent discovery pipeline . they propose to utilize conversational structure of real-life datasets for clustering . |
| Outcome: | The proposed method gives 33pp performance boost over state-of-the-art model for question only . it also gives 13pp performance increase over the naive baseline model . |
KLEJ: Comprehensive Benchmark for Polish Language Understanding (2020.acl-main)
Copied to clipboard
| Challenge: | Recent introduction of robust, general-purpose models for fine-tuning has enabled improvements in general natural language understanding (NLU) but such benchmarks are only available for a handful of languages. |
| Approach: | They propose a multi-task benchmark for the Polish language understanding with an online leaderboard . they also propose GLUE, a task for named entity recognition and sentiment analysis . |
| Outcome: | The proposed model performs best on three out of nine tasks in the Polish language . the proposed model is also used in an e-commerce domain to analyze the sentiments of users . |
Evaluation of Transfer Learning for Polish with a Text-to-Text Model (2022.lrec-1)
Copied to clipboard
Aleksandra Chrabrowa, Łukasz Dragan, Karol Grzegorczyk, Dariusz Kajtoch, Mikołaj Koszowski, Robert Mroczkowski, Piotr Rybak
| Challenge: | Recent years have brought significant progress in natural language understanding (NLU) and natural language generation (NLG). |
| Approach: | They propose a benchmark for assessing the quality of text-to-text models for Polish . they evaluate the performance of plT5, mT5, Polish BART, and Polish GPT-2 . |
| Outcome: | The proposed model can be fine-tuned on various NLP tasks with a single training objective. |