Entanglement-Optimal Fine-Tuning: Leveraging Structural Concept Coupling for Parameter-Efficient Adaptation
Entanglement-Optimal Fine-Tuning: Leveraging Structural Concept Coupling for Parameter-Efficient Adaptation
Structural entanglement predicts fine-tuning interference proportional to crosstalk between domains. 8-seed strong-intervention replication shows B3 (code+NL) drives entanglement intensity to zero in all Qwen-32B seeds — a sharp phase transition at steps 2000-3500. Cross-family replication on CodeLlama-7B and DeepSeek-Coder-6.7B confirms the collapse is Qwen-specific. Probe validation with three independent sets (including 132 real-dataset probes) confirms the collapse is genuine geometric destruction. CSR (complement-subspace regularization) preserves structure with 95% CI spanning zero.
Paper 44 in the Structural Compression Theory research program by Jeremy McEntire. V2: Added 8-seed strong-intervention replication, cross-family replication (CodeLlama, DeepSeek), and probe validation. Renamed from Universal to Structural entanglement.
Qwen, entanglement-optimal, cross-family replication, phase transition, complement-subspace regularization, structural entanglement, CodeLlama, DeepSeek, fine-tuning, QLoRA
Qwen, entanglement-optimal, cross-family replication, phase transition, complement-subspace regularization, structural entanglement, CodeLlama, DeepSeek, fine-tuning, QLoRA
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