RCCM: Diagnosing Gains and Harms in Reasoning-Prompt Transfer

arXiv:2610.19872v1 Announce Type: new Abstract: A reasoning prompt can improve one deployment and degrade another. RCCM (Reasoning-Control Capability Mismatch) examines these reversals by pairing answers to the same questions with records of how generation ends. Across five open-weight deployments and nine strategies, aggregate accuracy hides substantial question-level gains and harms; a common-budget MATH500 evaluation examines transfer on a separate sample. On 60 additional questions, concise reasoning improves Phi's automatic answer matching at a 2,048-token cap across three collections, but sharply reduces Qwen's. Author-reviewed final-answer commitments give a smaller, statistically unresolved Phi gain. Reserving an answer stage also improves matching, with additional input and call costs. These results show why a prompt benefit must be interpreted alongside its execution and evaluation: matching a reference answer need not mean delivering it, and an apparent compression benefit may admit another explanation. RCCM records this evidence for reproducible transfer comparisons.

Related

• Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?
• Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models
• SICI: A Semantic-Pragmatic Complexity Index Reveals Regime Shifts in LLM Stance Detection
• Prompt-Induced Waste in Large Reasoning Models: A Preregistered Two-Harness Benchmark of Coding Agents

Source: arXiv cs.CL | 2026-10-15