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From the last month
SDPO fused kernel for distillation silently drops importance sampling correction
python sdpo importance-sampling fused-kernel off-policy-correction 118 tokens
SDPO/DPO KL Regularization Training Collapse with LORA on SFT Adapted Model
python sdpo dpo kl-regularization training-collapse 96 tokens
SDPO: KL divergence regularization causes model collapse (degenerate output) despite anchor fix
python sdpo dpo kl-divergence model-collapse 65 tokens
ReLoRA SDPO training shows diminishing returns after first generation
python relora sdpo distillation diminishing-returns 141 tokens
SDPO training Gemma 4 31B with ReLoRA: KL divergence explodes when kl_reg > 0
python relora sdpo lora kl-divergence 150 tokens
SDPO Python: Style Auxiliary Loss Fails to Prevent Batch Style Drift During Distillation
python sdpo auxiliary-loss style-transfer mmd 130 tokens
SDPO teacher cache: pre-compute deterministic forward passes to eliminate redundant GPU work
python sdpo distillation training gpu-optimization 327 tokens
Python SDPO voice cloning: Hindsight teacher loss causes regression to base model distribution
python sdpo self-distillation voice-cloning fine-tuning 81 tokens
Python SDPO: Fused kernel implementation of CLaaS distillation misses off-policy importance-sampling ratio clipping
python sdpo claas distillation fused-kernel 781 tokens
SDPO CLaaS KL regularization overflow with DPO-trained LoRA on Gemma-4-31B-it
python sdpo claas distillation kl-regularization 301 tokens
Unsloth FastLanguageModel supports peft's model.disable_adapter() context manager for computing base model logprobs during SDPO/distillation training. This is not documented but works because Unsloth
python unsloth peft lora sdpo 69 tokens +1