RobotValues is a benchmark of 10K value-conflict scenarios that reveals VLMs default to safety and accommodation while failing to follow instructions to prioritize other values 80% of the time.
Value FULCRA : Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Value
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Context and retrieved moral knowledge improve sentence-level Schwartz value detection more consistently than model scaling, with early-fusion RAG outperforming other variants in matched comparisons.
Teachers' views on AI benefits and risks vary widely across 55 countries, but LLMs compress these differences, overestimate both sides, and show little improvement from country prompting or better reasoning.
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