6 papers
Class-aware Latent Attention Replay (CLAR): Class Incremental Hazard Diagnosis for Resilient AI in the Manufacturing Industrial Internet
Avranshu Mahanty, Ran Jin, Yingyan Zeng
Artificial Intelligence (AI) systems provide critical computation services in the Manufacturing Industrial Internet (MII), and their resilience depends on timely diagnosis of hazar…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +378
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
Robust Joint Modeling for Data with Continuous and Binary Responses
Yu Wang, Ran Jin, Lulu Kang
In many supervised learning applications, the response consists of both continuous and binary outcomes. Studies have shown that jointly modeling such mixed-type responses can subst…
Hierarchical Dataset Selection for High-Quality Data Sharing
Xiaona Zhou, Yingyan Zeng, Ran Jin +1
The success of modern machine learning hinges on access to high-quality training data. In many real-world scenarios, such as acquiring data from public repositories or sharing acro…
Ensemble Active Learning by Contextual Bandits for AI Incubation in Manufacturing
Yingyan Zeng, Xiaoyu Chen, Ran Jin
It is challenging but important to save annotation efforts in streaming data acquisition to maintain data quality for supervised learning base learners. We propose an ensemble acti…
ModelPred: A Framework for Predicting Trained Model from Training Data
Yingyan Zeng, Jiachen T. Wang, Si Chen +3
In this work, we propose ModelPred, a framework that helps to understand the impact of changes in training data on a trained model. This is critical for building trust in various s…