Source record

Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2608.26715.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

RegulAR is an AR task assistant that models procedural tasks as hierarchical dependency graphs and combines this with a multimodal LLM to track progress, classify errors by type, estimate their downstream impact, and deliver recovery guidance through a head-up display. A 12-person within-subject study reported better task-structure understanding and recovery support versus an MLLM-only baseline.

Concrete pattern for pairing structured task graphs with an MLLM so agents can reason about procedural deviations, not just the next step. Relevant to anyone designing workflow agents that must detect and recover from user errors.

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