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NARU is a benchmark for evaluating narrative evolution and cultural reasoning in Japanese extreme long-form videos, constructed through a hierarchical annotation pipeline and native-speaker verification to address gaps in current benchmarks.
SwanNLP presents an LLM-based framework for plausibility scoring in narrative word sense disambiguation at SemEval-2026 Task 5, using structured reasoning and dynamic few-shot prompting to predict human-perceived plausibility of word senses in short stories. The work demonstrates that commercial large-parameter LLMs with few-shot prompting and model ensembling effectively replicate human judgment patterns in realistic narrative contexts.