1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Interactive Training 2: Auditable Control Plane for Live Model Training
Wentao Zhang, Xuanhe Pan, Han Zhou +2
Experiment trackers show how training is progressing, but changing a live run still usually requires trainer-specific code. We present Interactive Training 2, an open-source contro…
cs.CV2025★ 1 cited
Anyone Can Jailbreak: Prompt-Based Attacks on LLMs and T2Is
Ahmed B Mustafa, Zihan Ye, Yang Lu +2
Despite significant advancements in alignment and content moderation, large language models (LLMs) and text-to-image (T2I) systems remain vulnerable to prompt-based attacks known a…
cs.CV2025
Progressive Data Dropout: An Embarrassingly Simple Approach to Faster Training
Shriram M Sathiyanarayanan, Xinyue Hao, Shihao Hou +4
The success of the machine learning field has reliably depended on training on large datasets. While effective, this trend comes at an extraordinary cost. This is due to two deeply…