The paper presents a novel approach, MultiRankIt, for a task defined as Learning-to-Rank Physical Objects (LTRPO). The task involves retrieving target objects from open-vocabulary user instructions in a human-in-the-loop setting….
Continue readingThe article discusses the problem of relevance ranking – sorting objects according to a given criterion. This is a challenge because different users may prefer different criteria, so the ranking…
Continue readingThis paper presents a new approach to optimizing cascade ranking systems, which are widely used in online advertising and recommendation systems. The authors propose the Adaptive Neural Ranking Framework (ARF),…
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