一作ICML 2026Poster· Social Aspects / Alignment
Position: Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences
Cristina Garbacea
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Cristina Garbacea
Cristina Garbacea · Heran Wang · Chenhao Tan
With the rise in capabilities of large language models (LLMs) and their deployment in real-world tasks, evaluating LLM alignment with human preferences has become an important challenge. Current benchmarks average preferences across all users to compute aggregate ratings, overlooking individual u...