Evidence Before Sampling: Interpretable Implicit Negative Candidate Discovery for Recommendation
Recommender systems learn from observed user-item interactions, but explicit negative feedback is often unavailable. Since deep learning models require negative signals for training, negative sampling methods typically treat selected unobserved interactions as negatives. However, a missing interaction does not explain...
Shreyaa Rajpal, Sonia Sharma, Swapnil Parekh et al.
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