Arctic-ABSA: Reasoning-Infused, Multilingual Sentiment Analysis for Real-World Use
Arctic-ABSA brings aspect-based sentiment analysis closer to real life. Instead of only “positive/negative/neutral,” it adds nuance, multilingual reach, and reasoning for better business decisions.
- Five classes: positive, negative, neutral, mixed, and unknown.
- Finds aspect-level opinions and the overall tone in one pass.
- Multilingual: one model holds 87–91% accuracy across six languages without hurting English.
- Reasoning-infused training: Chain-of-Thought examples plus a new reasoning pretraining for encoder models improve fine-tuning and generalization.
- Scale: trained on a corpus about 20× larger than SemEval14 (public + carefully generated synthetic data).
- Benchmarking: introduces ABSA-mix, aggregating 17 public datasets across 92 domains.
- Performance: a 395M encoder and an 8B decoder set new SOTA on SemEval14; the authors report up to 10-point accuracy gains over GPT-4o and Claude 3.5 Sonnet.
By Paweł Liskowski and Krzysztof Jankowski. Read more: https://arxiv.org/abs/2601.03940v1
Paper: https://arxiv.org/abs/2601.03940v1
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NLP SentimentAnalysis AI LLM ABSA Multilingual Reasoning Benchmark
