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Summaries of literary works often distort the original narrative, with human and LLM annotators both failing to maintain linearity and uniformity in their representations.
Multilingual embeddings that seem to encode language proficiency in one dataset completely fail to generalize to others, suggesting they're picking up dataset-specific artifacts, not true proficiency.
