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Found 3 papers, 2 papers with code
Few-Shot Learning on Graphs: from Meta-learning to Pre-training and Prompting
Finally, we outline prospective future directions for few-shot learning on graphs to catalyze continued innovation in this field.
Actively Discovering New Slots for Task-oriented Conversation
Existing task-oriented conversational search systems heavily rely on domain ontologies with pre-defined slots and candidate value sets.
Multi-Sample based Contrastive Loss for Top-k Recommendation
Therefore, we propose a Multi-Sample based Contrastive Loss (MSCL) function which solves the two problems by balancing the importance of positive and negative samples and data augmentation.
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