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Skeleton-based reasoning prompting is a promising training-free approach for structuring LLM reasoning, but prior work largely assumes an English-centric setting. We propose the Language-Aware Skeleton Exploration Framework (LASEF) to study skeleton-language choice in multilingual mathematical reasoning. Across math be...
MELON is introduced, the first large-scale dataset designed to extend text-video retrieval to long-form videos featuring complex, multi-event structures, and a multi-event aware loss is proposed that encourages models to differentiate between full-event and partial-event matches, yielding substantial improvements in re...
This work constructs a pipeline in which a misaligned teacher model generates filtered synthetic datasets across domains such as creative writing and code generation, which are then used to fine-tune aligned student models, and shows that benign-looking synthetic data can act as a covert channel for transmitting target...
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