2 papers
cs.CL2024
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.LG2020
-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers
Dionysis Manousakas, Cecilia Mascolo
Modern machine learning applications should be able to address the intrinsic challenges arising over inference on massive real-world datasets, including scalability and robustness…