mlsanityData to 7 Oct 2026

Advancing Cross-lingual Aspect-Based Sentiment Analysis with LLMs and Constrained Decoding for Sequence-to-Sequence Models

arXiv 2508.10366 ↗First posted 14 Aug 2025cs.CLcited by 3

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Abstract (arXiv)

Aspect-based sentiment analysis (ABSA) has made significant strides, yet challenges remain for low-resource languages due to the predominant focus on English. Current cross-lingual ABSA studies often centre on simpler tasks and rely heavily on external translation tools. In this paper, we present a novel sequence-to-sequence method for compound ABSA tasks that eliminates the need for such tools. Our approach, which uses constrained decoding, improves cross-lingual ABSA performance by up to 10%. This method broadens the scope of cross-lingual ABSA, enabling it to handle more complex tasks and providing a practical, efficient alternative to translation-dependent techniques. Furthermore, we compare our approach with large language models (LLMs) and show that while fine-tuned multilingual LLMs can achieve comparable results, English-centric LLMs struggle with these tasks.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 20 of its 38 references that are in the map. First posted on arXiv 14 Aug 2025.

Builds on

20 of 38 references.

References · 20

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8 more
  1. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 262
  2. 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 99
  3. 2023MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Predictioncited by 49
  4. 2022Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentationcited by 29
  5. 2020Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyondcited by 22
  6. 2019Zero-Shot Cross-Lingual Opinion Target Extractioncited by 11
  7. 2022CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysiscited by 6
  8. 2025LLaMA-Based Models for Aspect-Based Sentiment Analysiscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Extending Czech Aspect-Based Sentiment Analysis with Opinion Terms: Dataset and LLM Benchmarkscited by 0
  2. 2026Zero-Shot to Full-Resource: Cross-lingual Transfer Strategies for Aspect-Based Sentiment Analysiscited by 0
  3. 2026Generative Models Enhanced by Sequence Labelling and Aspect-Code Switching Improve Cross-lingual Aspect-Based Sentiment Analysiscited by 0