4 citations · 4 across the 5 of their papers we have counts for
5 papers
Text is All You Need for Vision-Language Model Jailbreaking
Yihang Chen, Zhao Xu, Youyuan Jiang +2
Large Vision-Language Models (LVLMs) are increasingly equipped with robust safety safeguards to prevent responses to harmful or disallowed prompts. However, these defenses often fo…
Learning label-label correlations in Extreme Multi-label Classification via Label Features
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis +3
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of label choices. Recent w…
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
Siddhant Kharbanda, Devaansh Gupta, Gururaj K +4
Extreme Multi-label Classification (XMC) involves predicting a subset of relevant labels from an extremely large label space, given an input query and labels with textual features.…
Federated Learning with Projected Trajectory Regularization
Tiejin Chen, Yuanpu Cao, Yujia Wang +2
Federated learning enables joint training of machine learning models from distributed clients without sharing their local data. One key challenge in federated learning is to handle…
Why Does Sharpness-Aware Minimization Generalize Better Than SGD?
Zixiang Chen, Junkai Zhang, Yiwen Kou +3
The challenge of overfitting, in which the model memorizes the training data and fails to generalize to test data, has become increasingly significant in the training of large neur…