Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents
Software-agent benchmarks usually report whether an agent solves a task, but the agent reaches that outcome through a harness that controls what it sees, which actions it can take, which failures are repaired, which states are verified, and which evidence is logged. We show that this harness can change the agent's multi-step beliefs even when the task, environment, and base LLM are fixed. We introduce a belief-rollout diagnostic that elicits structured K-step trajectories over progress, risk, re
Record details
Published: 5 July 2026
Source: arXiv
Category: Research
Topics: Healthcare · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (5 July 2026), “Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents,” evidence record 221, https://ethics.ai/record/221 (originally published by arXiv).
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