most citedTraining Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability

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cs.CL2024★ 2 cited

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability

Jiri Hron, Laura Culp, Gamaleldin Elsayed +28

While many capabilities of language models (LMs) improve with increased training budget, the influence of scale on hallucinations is not yet fully understood. Hallucinations come i…

cs.CL2024

Training LLMs over Neurally Compressed Text

Brian Lester, Jaehoon Lee, Alex Alemi +4

In this paper, we explore the idea of training large language models (LLMs) over highly compressed text. While standard subword tokenizers compress text by a small factor, neural t…