Goal-Conditioned Supervised Learning for LLM Fine-Tuning

In three linesNew offline fine-tuning method for LLMs: Goal-Conditioned Supervised Learning (GCSL). Treats feedback signals as explicit goals and trains models through pure supervised learning, without external reward models. Evaluated on non-toxic generation, code generation, and recommendation tasks.

Summary generated by Claude — human-verified