AIBearisharXiv – CS AI · May 297/10
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When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
A new study reveals that human curation efforts to align AI models can backfire in multi-model ecosystems where models train on outputs from other models. While curation improves alignment in isolated systems, cross-model interactions can dampen or reverse these benefits, potentially degrading long-term alignment across interconnected AI systems.