56 citations · 257 across the 54 of their papers we have counts for
8 papers · 2 filters
Learning to Compose SuperWeights for Neural Parameter Allocation Search
Piotr Teterwak, Soren Nelson, Nikoli Dryden +3
Neural parameter allocation search (NPAS) automates parameter sharing by obtaining weights for a network given an arbitrary, fixed parameter budget. Prior work has two major drawba…
CLAMP: Contrastive LAnguage Model Prompt-tuning
Piotr Teterwak, Ximeng Sun, Bryan A. Plummer +2
Large language models (LLMs) have emerged as powerful general-purpose interfaces for many machine learning problems. Recent work has adapted LLMs to generative visual tasks like im…
From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition
Maan Qraitem, Kate Saenko, Bryan A. Plummer
Visual recognition models are prone to learning spurious correlations induced by a biased training set where certain conditions (\eg, Indoors) are over-represented in certain c…
Multiscale Video Pretraining for Long-Term Activity Forecasting
Reuben Tan, Matthias De Lange, Michael Iuzzolino +4
Long-term activity forecasting is an especially challenging research problem because it requires understanding the temporal relationships between observed actions, as well as the v…
LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration
Siqi Wang, Bryan A. Plummer
Learning with noisy labels (LNL) aims to train a high-performing model using a noisy dataset. We observe that noise for a given class often comes from a limited set of categories,…
Text-to-image Editing by Image Information Removal
Zhongping Zhang, Jian Zheng, Jacob Zhiyuan Fang +1
Diffusion models have demonstrated impressive performance in text-guided image generation. Current methods that leverage the knowledge of these models for image editing either fine…