Answer configuration determines whether LLMs follow their reasoning trace or current evidence
The arXiv preprint (2610.20805v1) studies how keeping a model's reasoning trace at answer time interacts with verified evidence by comparing two answer configurations: continuation of the model's own thinking versus a separate answer call. Across gpt-oss, Gemma4 and Qwen3 on HotpotQA and MuSiQue, using a separate answer call raises evidence-following by 29.9–60.6 points versus continuation; removing the trace lowers accuracy similarly under both configurations, but continuation disproportionately repeats stale conclusions while a separate call follows current evidence far more often. The paper also finds that the final line of a trace carries most of its value, gold evidence helps most before the trace is written, distractors weaken correction under a separate call, and renewed reasoning (as opposed to a verification instruction) typically follows current evidence in conflicts, leading the authors to recommend reporting both trace benefit and evidence-following alongside answer configuration when evaluating traces.