Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces
Language models often generate long chain-of-thought traces, but it remains unclear how much of this reasoning is necessary for preserving the final prediction. We study this through the lens of overcomplete reasoning traces: generated traces that contain more intermediate steps than are needed to support the model's answer. We define the minimal core as the smallest subset of steps that preserves either the final answer or predictive distribution, and introduce metrics for compression ratio, redundancy mass, step necessity, and necessity concentration. Across six deliberative reasoning benchmarks spanning arithmetic, competition mathematics, expert scientific reasoning, and commonsense m...
| Authors | Sanjoy Chowdhury, Dinesh Manocha |
|---|---|
| Primary category | cs.AI |
| Published | 14 May 2026 |
| Last updated at source | 14 May 2026 |
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