Geometry-Aware Test-Time Learning for Quantitative Spatial Reasoning
TTL-SR is proposed, a geometry-aware Test-Time Learning framework for quantitative Spatial Reasoning that leverages geometric consistency constraints and unlabeled test data to adapt models to target domains to boost spatial reasoning performance.
Ge-Ge Zhang, Shuai-Cheng Niu, Gang Dai et al.
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