Shuyang Gu

Streamlining Long-Chain Reasoning via Differentiable Hierarchical Fusion

Differentiable Hierarchical Fusion is presented, a novel framework that merges reasoning models with efficient base models via differentiable optimization to produce concise, accurate outputs and introduces a dual-factor adaptive weighting mechanism to capture intra-block variance and inter-block importance hierarchies, thereby addressing key limitations of static merging heuristics.