Tag: data sparsity

A zero-shot evaluation of GPT-4o found strong performance for chemical incident extraction from news articles, while radiological events were too ...

Researchers have introduced an on-demand data augmentation framework that identifies sparse multi-dimensional intervals and topics to generate realistic synthetic samples ...

A new study reports a quantum-inspired recommendation system combining fuzzy clustering, generative adversarial networks, and a dandelion-based optimizer that achieved ...

A new graph-based framework groups similar learners and augments sparse data to improve cognitive diagnosis predictions across three public datasets.

Researchers have introduced HOFA, a contrastive learning framework that mines triangular motifs in social networks and aligns embedding features to ...

A new hybrid framework called LLMTransRec combines transformer sequence modeling with large language model embeddings to improve recommendations across sparse ...

Self-supervised learning (SSL) has gained recognition as a transformative approach for effectively extracting meaningful representations from extensive unlabelled datasets in ...