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    <abstract>This paper presents an uncertainty-aware adversarial learning framework developed for SemEval-2026 Task 3, a shared task focusing on Dimensional Aspect-Based Sentiment Analysis (ABSA). Our framework involves three key components: Uncertainty modeling, Heterogeneous Mixture-of-Experts (HMoE) architecture, and embedding-level adversarial training. Experimental results demonstrate that our framework effectively reduces the Root Mean Square Error (RMSE), thereby validating the synergistic advantages of uncertainty modeling and heterogeneous fusion strategies in fine-grained sentiment regression tasks.</abstract>
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%0 Conference Proceedings
%T Scmhl5 at SemEval-2026 Task 3: Uncertainty-Aware Adversarial Learning for Embedding Enhancement in Dimensional Aspect-Based Sentiment Analysis
%A Chen, Haohuan
%A Liu, Han
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F chen-liu-2026-scmhl5
%X This paper presents an uncertainty-aware adversarial learning framework developed for SemEval-2026 Task 3, a shared task focusing on Dimensional Aspect-Based Sentiment Analysis (ABSA). Our framework involves three key components: Uncertainty modeling, Heterogeneous Mixture-of-Experts (HMoE) architecture, and embedding-level adversarial training. Experimental results demonstrate that our framework effectively reduces the Root Mean Square Error (RMSE), thereby validating the synergistic advantages of uncertainty modeling and heterogeneous fusion strategies in fine-grained sentiment regression tasks.
%U https://aclanthology.org/2026.semeval-1.222/
%P 1748-1754

Markdown (Informal)

[Scmhl5 at SemEval-2026 Task 3: Uncertainty-Aware Adversarial Learning for Embedding Enhancement in Dimensional Aspect-Based Sentiment Analysis](https://aclanthology.org/2026.semeval-1.222/) (Chen & Liu, SemEval 2026)

• Scmhl5 at SemEval-2026 Task 3: Uncertainty-Aware Adversarial Learning for Embedding Enhancement in Dimensional Aspect-Based Sentiment Analysis (Chen & Liu, SemEval 2026)

ACL

• Haohuan Chen and Han Liu. 2026. Scmhl5 at SemEval-2026 Task 3: Uncertainty-Aware Adversarial Learning for Embedding Enhancement in Dimensional Aspect-Based Sentiment Analysis. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 1748–1754, San Diego, California, USA. Association for Computational Linguistics.