10 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Position: The Most Expensive Part of an LLM should be its Training Data
Nikhil Kandpal, Colin Raffel
Training a state-of-the-art Large Language Model (LLM) is an increasingly expensive endeavor due to growing computational, hardware, energy, and engineering demands. Yet, an often-…
cs.CR2023★ 10 cited
Backdoor Attacks for In-Context Learning with Language Models
Nikhil Kandpal, Matthew Jagielski, Florian Tramèr +1
Because state-of-the-art language models are expensive to train, most practitioners must make use of one of the few publicly available language models or language model APIs. This…
cs.LG2023★ 5 cited
Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models
Nikhil Kandpal, Brian Lester, Mohammed Muqeeth +6
Currently, most machine learning models are trained by centralized teams and are rarely updated. In contrast, open-source software development involves the iterative development of…