3 citations · 8 across the 12 of their papers we have counts for
12 papers
Do More Predictions Improve Statistical Inference? Filtered Prediction-Powered Inference
Shirong Xu, Will Wei Sun
Recent advances in artificial intelligence have enabled the generation of large-scale, low-cost predictions with increasingly high fidelity. As a result, the primary challenge in s…
Optimal Watermark Generation under Type I and Type II Errors
Hengzhi He, Shirong Xu, Alexander Nemecek +3
Watermarking has recently emerged as a crucial tool for protecting the intellectual property of generative models and for distinguishing AI-generated content from human-generated d…
Human-Corrected Labels Learning: Enhancing Labels Quality via Human Correction of VLMs Discrepancies
Zhongnian Li, Lan Chen, Yixin Xu +2
Vision-Language Models (VLMs), with their powerful content generation capabilities, have been successfully applied to data annotation processes. However, the VLM-generated labels e…
A Probabilistic Perspective on Model Collapse
Shirong Xu, Hengzhi He, Guang Cheng
In recent years, model collapse has become a critical issue in language model training, making it essential to understand the underlying mechanisms driving this phenomenon. In this…
Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework
Hengzhi He, Shirong Xu, Guang Cheng
Recent studies identified an intriguing phenomenon in recursive generative model training known as model collapse, where models trained on data generated by previous models exhibit…
Consistent community detection in multi-layer networks with heterogeneous differential privacy
Yaoming Zhen, Shirong Xu, Junhui Wang
As network data has become increasingly prevalent, a substantial amount of attention has been paid to the privacy issue in publishing network data. One of the critical challenges f…
TimeAutoDiff: A Unified Framework for Generation, Imputation, Forecasting, and Time-Varying Metadata Conditioning of Heterogeneous Time Series Tabular Data
Namjoon Suh, Yuning Yang, Din-Yin Hsieh +4
We present TimeAutoDiff, a unified latent-diffusion framework for four fundamental time-series tasks: unconditional generation, missing-data imputation, forecasting, and time-varyi…
Discriminative Estimation of Total Variation Distance: A Fidelity Auditor for Generative Data
Lan Tao, Shirong Xu, Chi-Hua Wang +2
With the proliferation of generative AI and the increasing volume of generative data (also called as synthetic data), assessing the fidelity of generative data has become a critica…
Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging
Wei Zhang, Xiangyuan Guan, Lu Yunhong +5
Logs produced by extensive software systems are integral to monitoring system behaviors. Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults.…
Rate-Optimal Rank Aggregation with Private Pairwise Rankings
Shirong Xu, Will Wei Sun, Guang Cheng
In various real-world scenarios, such as recommender systems and political surveys, pairwise rankings are commonly collected and utilized for rank aggregation to derive an overall…
Utility Theory of Synthetic Data Generation
Shirong Xu, Will Wei Sun, Guang Cheng
Synthetic data algorithms are widely employed in industries to generate artificial data for downstream learning tasks. While existing research primarily focuses on empirically eval…
Ranking Differential Privacy
Shirong Xu, Will Wei Sun, Guang Cheng
Rankings are widely collected in various real-life scenarios, leading to the leakage of personal information such as users' preferences on videos or news. To protect rankings, exis…