Recursive Multimodal Data Reveals New Collapse Modes

Observed now: Researchers studying recursive multimodal generate-train loops find degradation and distribution effects, including altered vision-language alignment, and test mitigation strategies. PaperBench separately demonstrates decomposed evaluation of complex research replication. Together they support rigorous auditing of synthetic-data experiments, without claiming deployed tools already detect duplication or provenance gaps.