Improving LLM Predictions via Inter-Layer Structural Encoders

ArXi:2603.22665v1 Announce Type: cross The standard practice in Large Language Models (LLMs) is to base predictions on the final-layer token representations. Recent studies, however, show that intermediate layers encode substantial information, which may contain task-relevant features than the final-layer representations alone. Importantly, it was shown that for different tasks, different layers may be optimal. In this work we