Doing What They Say, Not What They Reason: Locating the Faithfulness Gap in LLM Agents
Do LLM agents act on the reasoning they state? This question of process fidelity is central to LLM-based social simulation, yet hard to measure where no reference for correct behavior exists. We study it in a controlled setting: a Texas Poker simulator with a verifiable reference action for every decision by splitting the faithfulness gap into two steps: reasoning-to-conclusion (does the stated decision follow from the agent's own reasoning?) and conclusion-to-action (does the agent execute what it states?). The two steps behave very differently. Conclusion-to-action is reliable: inconsistency is 0.7% for Claude Haiku 4.5 and 1.4% for DeepSeek-Reasoner once the conclusion is read from an ...
| Authors | Yufeng Wang |
|---|---|
| Primary category | cs.AI |
| Published | 30 May 2026 |
| Last updated at source | 6 July 2026 |
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