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A learned shortlist can achieve private dense retrieval with accuracy and efficiency, cutting processing time by nearly 10% while preserving query confidentiality.
Full-context interventions in Decision Transformers can dramatically shift predictions, but the effectiveness is highly dataset-dependent, revealing potential pitfalls in RTG conditioning.
CVLNet reveals that urban perception mapping can be achieved at scale without relying on limited street view imagery, significantly enhancing our understanding of urban environmental inequality.
