An LLM-native five-factor psychometric instrument produces stable self-report structure but fails to predict observed behavior, and reveals a shared textual-surface bias between self-report and LLM judges that human raters do not share.
On the creativity of large language models
4 Pith papers cite this work. Polarity classification is still indexing.
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LLM translations introduce model-specific statistically significant emotional fingerprints that limit preservation of author voice, with post-editing providing partial alignment to human norms.
Uses digital humanities corpus analysis on 2024 AI literature to map epistemic virtues and outline a generativity-centered framework for evaluating AI knowledge-worth.
GPT-4o produces humorous and relevant cartoon captions in many cases but frequently misses irony, cultural references, or narrative constraints, supporting its use as an ideation assistant in hybrid human-AI workflows.
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Emotion Profiling in LLM-Based Literary Translation: Systematic Shifts Across MT and Post-Editing
LLM translations introduce model-specific statistically significant emotional fingerprints that limit preservation of author voice, with post-editing providing partial alignment to human norms.