arXiv: cs.AI preprintsInternational6 November 2026
ReferClaw: Disambiguating User Intent for Egocentric Assistance
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arXiv:2611.07683v1 Announce Type: cross Abstract: Users of egocentric AI assistants often ask short, ambiguous questions whose intended referents cannot be uniquely resolved from video and dialogue history. For example, "Where did I leave it?" may refer to several previously handled objects. Existing VideoQA systems typically commit to a single interpretation, risking plausible but intention-misaligned answers. We introduce ReferClaw, an agentic framework that formulates egocentric streaming QA as an interactive process: the assistant asks clarifying questions to resolve user intent before ans
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