most citedSmall-scale proxies for large-scale Transformer training instabilities

4 citations · 7 across the 4 of their papers we have counts for

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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.CL2023

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?

C. Daniel Freeman, Laura Culp, Aaron Parisi +27

We introduce and study the problem of adversarial arithmetic, which provides a simple yet challenging testbed for language model alignment. This problem is comprised of arithmetic…