Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions
Deep Research agents conduct long-horizon investigations by iteratively planning, retrieving evidence, and generating reports. However, it remains unclear whether they can resist apparently credible but factually false information introduced into these workflows. To study this failure mode, we introduce MisKnow-Agent, a controlled evaluation framework that constructs task-specific documents supporting manually audited false conclusions with controlled authority cues and source styles. Applied to the tasks from DeepResearch Bench, it generates 5,933 misleading documents after filtering. We evaluate DeerFlow and WebThinker with three backbone LLMs, together with Gemini Deep Research, using ...
| Authors | Pengyu Zhu, Lijun Li, Longju Yang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 23 July 2026 |
| Last updated at source | 30 July 2026 |
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