TL;DR
UIT-Polar system achieves Top-5 results on the English test set, demonstrating the effectiveness of integrating encoder-based screening with LLM-based refinement.
This approach combines option-permutation augmentation for Chinese data, annotator vote expansion for Indonesian data, and binary reformulation with SinhalaMMLU augmentation with SinhalaMMLU augmentation for Sri Lankan data to focus on pluralistic value alignment in the contexts of China, Indonesia, and Sri Lanka.
This paper presents the winning system for SemEval-2026 Task 5 on rating the plausibility of word senses in ambiguous stories, demonstrating the effectiveness of unified regressive–generative modeling for fine-grained plausibility estimation.
This paper details the Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice Question Answering (MCQA) across 21 languages. Three approaches are explored. First, we fine-tune Voxtral-Mini-3B via LoRA with cross-lingual data augmentation, ASR tr...
This work studies a variety of retrieval-based in-context learning (RetICL) strategies for detecting defamatory offences under {\S}{\S} 185-187 StGB (the subject of GermEval 2026 Subtask 4).
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