5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2024
vTune: Verifiable Fine-Tuning for LLMs Through Backdooring
Eva Zhang, Arka Pal, Akilesh Potti +1
As fine-tuning large language models (LLMs) becomes increasingly prevalent, users often rely on third-party services with limited visibility into their fine-tuning processes. This…
cs.AI2023★ 5 cited
Giraffe: Adventures in Expanding Context Lengths in LLMs
Arka Pal, Deep Karkhanis, Manley Roberts +3
Modern large language models (LLMs) that rely on attention mechanisms are typically trained with fixed context lengths which enforce upper limits on the length of input sequences t…