SemEval2024-task 11: Bridging the Gap in Text-Based Emotion Detection
[ACL 2025] Knowledge Unlearning for Large Language Models
This is the official repository of Team Anastasia, which achieved 1st place in Subtask 1 of the SemEval 2025 challenge.
This is the repository of the MyMy team, ranked Top 2 in Subtask 1 and Top 2 in Subtask 2 at the SemEval 2025 Task 9: Food Hazard Detection Challenge.
DNB-AI-Project at SemEval-2025 Task 5: An LLM-Ensemble Approach for Automated Subject Indexing
This repository is for the paper UAlberta at SemEval-2025 Task 2: Prompting and Ensembling for Entity-Aware Translation. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 1709–1717, Vienna, Austria. Association for Computational Linguistics.
Official implementation for SemEval-2025 Task 9: Food Hazard Detection. Features a Multimodal Ensemble of BERT, RoBERTa, and SVM.
NLP pipelines for SemEval-2025 Task 10 - entity framing and narrative classification in online news, comparing classical ML, DistilBERT, and LLaMA-3.2-3B with LoRA.
Evaluation toolkit and analysis for English-to-Korean entity-aware machine translation, comparing automatic metrics, model baselines, and Korean human judgments on named-entity fidelity.
Solution for SemEval-2025 Task 9: The Food Hazard Detection Challenge. Utilized machine learning, fine-tuned LLMs (GPT-2, LLaMA, Flan-T5-XL), and ensemble learning to classify food hazards and detect specific products and hazards from unstructured text.
A seminar project for PV057 Machine Learning and Data Mining class.
SemEval 2025 Task 3: Mu-SHROOM, the Multilingual Shared-task on Hallucinations and Related Observable Overgeneration Mistakes
SemEval-2026 Task 5 — Graded word-sense plausibility rating via a 3-component ensemble: zero-shot NLI, gloss-informed DeBERTa regressor, and a novel Likert-distribution head with uncertainty estimation.
Participation in SemEval 2025 Task 9: The Food Hazard Detection Challenge. [Official SemEval 2025 Task 9 GitHub]:
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