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cs.CL2026
Scaffold-Mediated Post-Training: Co-Evolving Model Parameters and Procedural Scaffold Graphs
Fei Ding, Yongkang Zhang, Runhao Liu +3
Post-training of large language models optimizes only parameters, while inference-time procedural scaffolds are typically designed independently of parameter training. This disconn…
cs.CL2025
Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgetting
Fei Ding, Baiqiao Wang
Supervised Fine-Tuning (SFT) is a critical step for enhancing the instruction-following capabilities of Large Language Models (LLMs) and adapting them to specialized domains. Howev…