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cs.AI2026
Drift-Constrained Optimization: Only Direction Matters in Fine-Tuning Instruct Models
Fei Yuan, Changjiang Gao, Yilei Tu +3
Fine-tuning instruct models often improves target performance while inducing behavioral drift from the reference model, which can degrade existing capabilities. Rather than treatin…
cs.AI2026
daVinci-LLM:Towards the Science of Pretraining
Yiwei Qin, Yixiu Liu, Tiantian Mi +12
The foundational pretraining phase determines a model's capability ceiling, as post-training struggles to overcome capability foundations established during pretraining, yet it rem…
cs.AI2026
Data Darwinism Part II: DataEvolve -- AI can Autonomously Evolve Pretraining Data Curation
Tiantian Mi, Dongming Shan, Zhen Huang +6
Data Darwinism (Part I) established a ten-level hierarchy for data processing, showing that stronger processing can unlock greater data value. However, that work relied on manually…