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Mistake Detection

Mistakes are natural occurrences in many tasks and an opportunity for an AR assistant to provide help. Identifying such mistakes requires modelling procedural knowledge and retaining long-range sequence information. In its simplest form Mistake Detection aims to classify each coarse action segment into one of the three classes: {“correct”, “mistake”, “correction”}.

Papers

Showing 1114 of 14 papers

TitleStatusHype
LLMs can Find Mathematical Reasoning Mistakes by Pedagogical Chain-of-Thought0
HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
Lexical Normalization of User-Generated Medical Text0
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