112 citations · 237 across the 20 of their papers we have counts for
5 papers · 1 filter
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni +10
Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…
Bring Your Own Data! Self-Supervised Evaluation for Large Language Models
Neel Jain, Khalid Saifullah, Yuxin Wen +6
With the rise of Large Language Models (LLMs) and their ubiquitous deployment in diverse domains, measuring language model behavior on realistic data is imperative. For example, a…
On the Exploitability of Instruction Tuning
Manli Shu, Jiongxiao Wang, Chen Zhu +3
Instruction tuning is an effective technique to align large language models (LLMs) with human intents. In this work, we investigate how an adversary can exploit instruction tuning…
On the Reliability of Watermarks for Large Language Models
John Kirchenbauer, Jonas Geiping, Yuxin Wen +7
As LLMs become commonplace, machine-generated text has the potential to flood the internet with spam, social media bots, and valueless content. Watermarking is a simple and effecti…
Hierarchical Point Attention for Indoor 3D Object Detection
Manli Shu, Le Xue, Ning Yu +5
3D object detection is an essential vision technique for various robotic systems, such as augmented reality and domestic robots. Transformers as versatile network architectures hav…