Structured State Reconciliation for Human-AI Task Handover
Task handover requires communicating enough current state for a successor to resume work, yet the relevant information is often divided between system records and human observations. System records can be precise and timestamped but only partially observe the task, while human reports capture intent and task knowledge that no log contains but are vulnerable to omission and memory error. We present a provenance-aware pipeline that converts task telemetry and human-authored reports into a shared typed task-state representation, aligns and reconciles their facts, detects conflicts, and generates structured handover reports. We evaluate the approach on 13 paired task states collected in a con...
| Authors | Kayleigh Bishop, Maria P. Stull, Breanne Crockett et al. |
|---|---|
| Primary category | cs.HC |
| Published | 28 August 2026 |
| Last updated at source | 28 August 2026 |
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