2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Large (Vision) Language Models are Unsupervised In-Context Learners
Artyom Gadetsky, Andrei Atanov, Yulun Jiang +4
Recent advances in large language and vision-language models have enabled zero-shot inference, allowing models to solve new tasks without task-specific training. Various adaptation…
cs.LG2024
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Foundation vision-language models have enabled remarkable zero-shot transferability of the pre-trained representations to a wide range of downstream tasks. However, to solve a new…
cs.LG2023★ 2 cited
The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
Artyom Gadetsky, Maria Brbic
We present HUME, a simple model-agnostic framework for inferring human labeling of a given dataset without any external supervision. The key insight behind our approach is that cla…