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Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News

arXiv 2303.01794 ↗First posted 3 Mar 2023cs.CL cs.AIcited by 0

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Abstract (arXiv)

This paper explains the participation of team Hitachi to SemEval-2023 Task 3 "Detecting the genre, the framing, and the persuasion techniques in online news in a multi-lingual setup.'' Based on the multilingual, multi-task nature of the task and the low-resource setting, we investigated different cross-lingual and multi-task strategies for training the pretrained language models. Through extensive experiments, we found that (a) cross-lingual/multi-task training, and (b) collecting an external balanced dataset, can benefit the genre and framing detection. We constructed ensemble models from the results and achieved the highest macro-averaged F1 scores in Italian and Russian genre categorization subtasks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 17 references that are in the map. First posted on arXiv 3 Mar 2023.

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References · 9

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  4. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  5. 2020Rethinking embedding coupling in pre-trained language modelscited by 103
  6. 2020Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Societycited by 72
  7. 2017This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real Newscited by 59
  8. 2020Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Armscited by 41
  9. 2019Hitachi at MRP 2019: Unified Encoder-to-Biaffine Network for Cross-Framework Meaning Representation Parsingcited by 2

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