mlsanityData to 14 Oct 2026

UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection

arXiv 2508.08650 ↗First posted 12 Aug 2025cs.CLcited by 1

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Abstract (arXiv)

This paper presents our system built for the WASSA-2024 Cross-lingual Emotion Detection Shared Task. The task consists of two subtasks: first, to assess an emotion label from six possible classes for a given tweet in one of five languages, and second, to predict words triggering the detected emotions in binary and numerical formats. Our proposed approach revolves around fine-tuning quantized large language models, specifically Orca~2, with low-rank adapters (LoRA) and multilingual Transformer-based models, such as XLM-R and mT5. We enhance performance through machine translation for both subtasks and trigger word switching for the second subtask. The system achieves excellent performance, ranking 1st in numerical trigger words detection, 3rd in binary trigger words detection, and 7th in emotion detection.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 26 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

14 of 26 references.

References · 14

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  5. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  6. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  7. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,127
  8. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 742
  9. 2014Recurrent Neural Network Regularizationcited by 189
  10. 2023Orca 2: Teaching Small Language Models How to Reasoncited by 159
  11. 2023Don't Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMscited by 104
  12. 2019Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classificationcited by 50
2 more
  1. 2020Cross-Lingual Semantic Role Labeling with High-Quality Translated Training Corpuscited by 49
  2. 2018IEST: WASSA-2018 Implicit Emotions Shared Taskcited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Generative Models Enhanced by Sequence Labelling and Aspect-Code Switching Improve Cross-lingual Aspect-Based Sentiment Analysiscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024TEII: Think, Explain, Interact and Iterate with Large Language Models to Solve Cross-lingual Emotion Detection
  2. 2024Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
  3. 2024EmoVerse: Exploring Multimodal Large Language Models for Sentiment and Emotion Understanding
  4. 2025Parallel Tokenizers: Rethinking Encoder Models' Vocabulary Design in Cross-Lingual Transfer of Low-Resource Languages
  5. 2026Disentangling Topology and Diversity in Multi-Agent LLMs for Multilingual Low-Resource Emotion Detection
  6. 2025Multi-Teacher Language-Aware Knowledge Distillation for Multilingual Speech Emotion Recognition
  7. 2025MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs
  8. 2026Extracting and Steering Emotion Representations in Small Language Models: A Methodological Comparison