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cs.AI2026
When Sample Selection Bias Precipitates Model Collapse
Xinbao Qiao, Xianglong Du, Wei Liu +4
The proliferation of recursive training on synthetic data can alleviate data scarcity but risks model collapse, where repeated training erodes distributional tails and homogenizes…
cs.AI2025
As If We've Met Before: LLMs Exhibit Certainty in Recognizing Seen Files
Haodong Li, Jingqi Zhang, Xiao Cheng +3
The remarkable language ability of Large Language Models (LLMs) stems from extensive training on vast datasets, often including copyrighted material, which raises serious concerns…