most citedQLoRA: Efficient Finetuning of Quantized LLMs

507 citations · 526 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20236 cited

How FaR Are Large Language Models From Agents with Theory-of-Mind?

Pei Zhou, Aman Madaan, Srividya Pranavi Potharaju +9

"Thinking is for Doing." Humans can infer other people's mental states from observations--an ability called Theory-of-Mind (ToM)--and subsequently act pragmatically on those infere…

cs.CY20231 cited

Artificial Intelligence and Aesthetic Judgment

Jessica Hullman, Ari Holtzman, Andrew Gelman

Generative AIs produce creative outputs in the style of human expression. We argue that encounters with the outputs of modern generative AI models are mediated by the same kinds of…

cs.LG20234 cited

Generative Models as a Complex Systems Science: How can we make sense of large language model behavior?

Ari Holtzman, Peter West, Luke Zettlemoyer

Coaxing out desired behavior from pretrained models, while avoiding undesirable ones, has redefined NLP and is reshaping how we interact with computers. What was once a scientific…

cs.LG2023507 cited

QLoRA: Efficient Finetuning of Quantized LLMs

Tim Dettmers, Artidoro Pagnoni, Ari Holtzman +1

We present QLoRA, an efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning t…

cs.CL20228 cited

What Do NLP Researchers Believe? Results of the NLP Community Metasurvey

Julian Michael, Ari Holtzman, Alicia Parrish +8

We present the results of the NLP Community Metasurvey. Run from May to June 2022, the survey elicited opinions on controversial issues, including industry influence in the field,…