71 citations · 128 across the 18 of their papers we have counts for
8 papers · 1 filter
TruncFormer: Private LLM Inference Using Only Truncations
Patrick Yubeaton, Jianqiao Cambridge Mo, Karthik Garimella +4
Private inference (PI) serves an important role in guaranteeing the privacy of user data when interfacing with proprietary machine learning models such as LLMs. However, PI remains…
Hidden in the Noise: Two-Stage Robust Watermarking for Images
Kasra Arabi, Benjamin Feuer, R. Teal Witter +2
As the quality of image generators continues to improve, deepfakes become a topic of considerable societal debate. Image watermarking allows responsible model owners to detect and…
SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification
Benjamin Feuer, Jiawei Xu, Niv Cohen +3
Data curation is the problem of how to collect and organize samples into a dataset that supports efficient learning. Despite the centrality of the task, little work has been devote…
Evaluation and Comparison of Visual Language Models for Transportation Engineering Problems
Sanjita Prajapati, Tanu Singh, Chinmay Hegde +1
Recent developments in vision language models (VLM) have shown great potential for diverse applications related to image understanding. In this study, we have explored state-of-the…
LiveBench: A Challenging, Contamination-Limited LLM Benchmark
Colin White, Samuel Dooley, Manley Roberts +15
Test set contamination, wherein test data from a benchmark ends up in a newer model's training set, is a well-documented obstacle for fair LLM evaluation and can quickly render ben…
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity
Chih-Hsuan Yang, Benjamin Feuer, Zaki Jubery +12
We introduce BioTrove, the largest publicly accessible dataset designed to advance AI applications in biodiversity. Curated from the iNaturalist platform and vetted to include only…
Agnostic Active Learning of Single Index Models with Linear Sample Complexity
Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu +3
We study active learning methods for single index models of the form , where and ${\mathb…
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova +5
While tabular classification has traditionally relied on from-scratch training, a recent breakthrough called prior-data fitted networks (PFNs) challenges this approach. Similar to…