--- title: "CITD@UIT at SemEval-2026 Task 2: Temporal" description: "The team from the University of Information Technology (VNU-HCM) built a system for SemEval-2026… 10 references, cited by 1 paper here." authors: ["Son The Phuong", "My Thuy-Tra Ngo", "Tri Minh Dao", "Duc-Vu Nguyen"] year: 2026 venue: "Proceedings of the 20th International Workshop on Semantic Evaluation (2026)" source: "https://aclanthology.org/2026.semeval-1.25/" doi: "10.18653/v1/2026.semeval-1.25" licence: "CC BY 4.0 (ACL Anthology)" licence_url: "https://creativecommons.org/licenses/by/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/phuong-2026-citd-uit-semeval-2026-task/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/phuong-2026-citd-uit-semeval-2026-task/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/11/) / CITD@UIT at SemEval-2026 Task 2: Temporal Mixture-of-Experts for Longitudinal Valence and Arousal Prediction from Ecological Essays # CITD@UIT at SemEval-2026 Task 2: Temporal Mixture-of-Experts for Longitudinal Valence and Arousal Prediction from Ecological Essays **Authors:** Son The Phuong, My Thuy-Tra Ngo, Tri Minh Dao and [Duc-Vu Nguyen](https://md.research.elamur.ai/free/en/authors/duc-vu-nguyen/) · **Year:** 2026 · **Venue:** [Proceedings of the 20th International Workshop on Semantic Evaluation (2026)](https://md.research.elamur.ai/free/en/venues/semeval/) ([SemEval 2026](https://md.research.elamur.ai/free/en/venues/semeval/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.semeval-1.25/) · [PDF](https://aclanthology.org/2026.semeval-1.25.pdf) · [DOI 10.18653/v1/2026.semeval-1.25](https://doi.org/10.18653/v1/2026.semeval-1.25) · [OpenAlex](https://openalex.org/W7166857357) **Citations:** 0 citations (OpenAlex, 2026-10-14) · [1](https://md.research.elamur.ai/free/en/papers/phuong-2026-citd-uit-semeval-2026-task/cited-by/) in our library, of the 149,439 papers whose bibliographies we read ## Summary The team from the University of Information Technology (VNU-HCM) built a system for SemEval-2026 Task 2, which models how a person's emotions change over time in their ecological essays. Subtask 1 asks for continuous Valence and Arousal scores for each text in a user's sequence. Subtask 2 asks for forecasts of short-term state change (2A) and long-term dispositional change (2B). The backbone is cardiffnlp/twitter-roberta-base-sentiment-latest. Posts are ordered by user and time, and consecutive posts are joined with a sliding window so the encoder sees recent history. For 2B, the text is split into past and future groups, and the mean past V&A values are fused into the representation late. The regression heads are either funnel-shaped MLPs or Mixture-of-Experts heads with sparse or soft gating. Features come from attention pooling or mean pooling. Training uses a joint CCC-based loss for both dimensions, which matches the task's evaluation metric. The system placed 9th in Subtask 1 and 5th in Subtask 2A. It did not generalize on 2B. The results suggest that expert routing helps short-horizon emotion forecasting, while long-range dispositional modeling remains difficult. ## Key points - The backbone, cardiffnlp/twitter-roberta-base-sentiment-latest, was pretrained on 124M tweets from 2018–2021. Each MLP head narrows from 768 to 256 to 128 to 1 dimensions, with separate branches for Valence and Arousal. - The MoE head has 4 experts. The sparse variant uses Top-k gating, and the soft variant uses dense softmax gating over all experts. The loss is the sum of (1 − CCC) for Valence and Arousal. - In Subtask 2A, Sparse MoE with Attention Pooling and a window of k = 8 ranked 5th of 15 teams. Its test r_avg was 0.631, slightly above its validation score of 0.623. - In Subtask 2B, Sparse MoE with Mean Pooling fell from 0.327 r_avg on validation to −0.114 on the blind test. The authors attribute this to three factors: - imbalance between the 768-dimensional text embedding and the 2-dimensional past-emotion features; - expert collapse; - overfitting given the small number of users. - Arousal was harder to predict than Valence. Code is available at github.com/PTSown0222/SemEval-2026-Task-2. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions - [Vietnam National University Ho Chi Minh City](https://md.research.elamur.ai/free/en/universities/vietnam-national-university-ho-chi-minh-city/) — University, Ho Chi Minh City, Vietnam · 21 works · 14 citations - [University of Information Technology](https://md.research.elamur.ai/free/en/universities/university-of-information-technology/) — University, Ho Chi Minh City, Vietnam · 13 works · 7 citations 📚 Shelves (5): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 18,614 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 17,965 works · [💭 Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/) · 1,649 works · [💭 Experimental and Cognitive Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · 930 works · [💭 Social Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) · 330 works 🧭 Topics (1): [😊 Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · 1,035 works ## Cite Cite as: Son The Phuong, My Thuy-Tra Ngo, Tri Minh Dao and Duc-Vu Nguyen. 2026. CITD@UIT at SemEval-2026 Task 2: Temporal Mixture-of-Experts for Longitudinal Valence and Arousal Prediction from Ecological Essays. Proceedings of the 20th International Workshop on Semantic Evaluation (2026). The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{phuong2026citd, title = {{CITD@UIT at SemEval-2026 Task 2: Temporal Mixture-of-Experts for Longitudinal Valence and Arousal Prediction from Ecological Essays}}, author = {Son The Phuong, My Thuy-Tra Ngo, Tri Minh Dao and Duc-Vu Nguyen}, booktitle = {Proceedings of the 20th International Workshop on Semantic Evaluation (2026)}, year = {2026}, doi = {10.18653/v1/2026.semeval-1.25}, url = {https://doi.org/10.18653/v1/2026.semeval-1.25} } ``` - [← previous CiNet-Handai-Kyodai at SemEval-2026 Task 5: Combining LLM Prompting, Semantic Similarity, and Synthetic Gaze for Graded Sense Plausibility](https://md.research.elamur.ai/free/en/papers/pereira-2026-cinet-handai-kyodai-semeval-2026/) - [next → CITD@UIT at SemEval-2026 Task 4: Structured Reasoning and Metric Specialization for Narrative Similarity](https://md.research.elamur.ai/free/en/papers/nguyen-2026-citd-uit-semeval-2026-task/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/11/) ## References 10 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. 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