3 papers
cs.LG2025
DropCluster: A structured dropout for convolutional networks
Liyan Chen, Philippos Mordohai, Sergul Aydore
Dropout as a common regularizer to prevent overfitting in deep neural networks has been less effective in convolutional layers than in fully connected layers. This is because Dropo…
cs.CL2025
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation
Tobias Leemann, Periklis Petridis, Giuseppe Vietri +3
While retrieval-augmented generation (RAG) has been shown to enhance factuality of large language model (LLM) outputs, LLMs still suffer from hallucination, generating incorrect or…
cs.IR2024
Language-Model Prior Overcomes Cold-Start Items
Shiyu Wang, Hao Ding, Yupeng Gu +3
The growth of recommender systems (RecSys) is driven by digitization and the need for personalized content in areas such as e-commerce and video streaming. The content in these sys…