Since CF model can memorize easy training instances first and gradually adapt to8 hard instances,a.k.a. After several training epochs, model iswell trained and evennew10 samplescanhavehighscores.11 Q3. how the std can be accurately estimated in Equation 4? And estimating std is expansive.Reply. In real applications, it is more important to rank the suitable items at top positions of a list. As suggested by reviewers, we list the rest results (K = 5/10)inthe following table. It can be observed that the proposed SRNS still outperformsvariousbaselines.

Few-shot in-context learning (ICL) enables pre-trained language models to perform apreviously-unseen task without anygradient-based training by feeding a small number of training examples as part of the input.

Partial multi-label learning aims to induce a multi-label predictor from inaccurately annotated examples, where a set of candidate labels is assigned to each training example but only some of thesecandidateonesarevalid.