Forward Pass Domain Adaptation (Without Cross-Layer Backpropagation)
Forward-Pass-Only (FPO) training enables efficient LLM adaptation by eliminating cross-layer backpropagation.
FPO training achieves 2.7–3.2x the throughput of standard fine-tuning with 40% less peak memory. By avoiding the backward pass through the model body, it maintains performance on off-domain benchmarks while significantly reducing computational overhead, offering a more stable alternative to full-network fine-tuning.