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LLMs struggle with procedural rule induction, revealing a significant performance gap that challenges current AI capabilities.
Despite recent advances, sign language translation models still struggle to leverage the full range of linguistic cues, especially non-manual signals like facial expressions.
Even when deprived of explicit hypernym examples during training, vision-language models can still generalize taxonomic relationships from images, revealing the surprising power of linguistic priors in cross-modal learning.
