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20212026
most citedVISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels

7 citations · 8 across the 11 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Evaluating Forecasting Techniques for Hardware Errors on a Large-scale HPC System

Kaiyuan Liao, Xiwei Xuan, Tanwi Mallick +3

Hardware error logs in high-performance computing (HPC) systems provide early signals of abnormal behavior, yet there remain challenges in effectively forecasting these errors usin…

cs.HC2026

Vibe Visualizing: How Visualization Novices Try (and Fail) to Generate and Interpret Visualizations with Conversational AI

Sam Yu-Te Lee, Yun-Hsin Kuo, Chifang Chou +3

Conversational AI has enabled users to generate and interpret visualizations through natural language, significantly lowering the technical barrier to entry. The increased accessib…

cs.CV2025★ 7 cited

VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels

Xiwei Xuan, Xiaoqi Wang, Wenbin He +4

The advances in multi-modal foundation models (FMs) (e.g., CLIP and LLaVA) have facilitated the auto-labeling of large-scale datasets, enhancing model performance in challenging do…

cs.CV2025

ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation

Xiwei Xuan, Ziquan Deng, Kwan-Liu Ma

Training-free open-vocabulary semantic segmentation (OVS) aims to segment images given a set of arbitrary textual categories without costly model fine-tuning. Existing solutions of…

cs.CV2025

VISLIX: An XAI Framework for Validating Vision Models with Slice Discovery and Analysis

Xinyuan Yan, Xiwei Xuan, Jorge Piazentin Ono +6

Real-world machine learning models require rigorous evaluation before deployment, especially in safety-critical domains like autonomous driving and surveillance. The evaluation of…

cs.CV2024

SLIM: Spuriousness Mitigation with Minimal Human Annotations

Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin +1

Recent studies highlight that deep learning models often learn spurious features mistakenly linked to labels, compromising their reliability in real-world scenarios where such corr…

cs.CV2024

USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation

Xiaoqi Wang, Wenbin He, Xiwei Xuan +8

The open-vocabulary image segmentation task involves partitioning images into semantically meaningful segments and classifying them with flexible text-defined categories. The recen…

cs.HC2024

A Reliable Framework for Human-in-the-Loop Anomaly Detection in Time Series

Ziquan Deng, Xiwei Xuan, Kwan-Liu Ma +1

Time series anomaly detection is a critical machine learning task for numerous applications, such as finance, healthcare, and industrial systems. However, even high-performing mode…

cs.CV2024★ 1 cited

AttributionScanner: A Visual Analytics System for Model Validation with Metadata-Free Slice Finding

Xiwei Xuan, Jorge Piazentin Ono, Liang Gou +2

Data slice finding is an emerging technique for validating machine learning (ML) models by identifying and analyzing subgroups in a dataset that exhibit poor performance, often cha…

cs.HC2023

LabelVizier: Interactive Validation and Relabeling for Technical Text Annotations

Xiaoyu Zhang, Xiwei Xuan, Alden Dima +2

With the rapid accumulation of text data produced by data-driven techniques, the task of extracting "data annotations"--concise, high-quality data summaries from unstructured raw t…

cs.CV2023

SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective

Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin +2

Researchers have proposed various methods for visually interpreting the Convolutional Neural Network (CNN) via saliency maps, which include Class-Activation-Map (CAM) based approac…

cs.LG2021

VAC-CNN: A Visual Analytics System for Comparative Studies of Deep Convolutional Neural Networks

Xiwei Xuan, Xiaoyu Zhang, Oh-Hyun Kwon +1

The rapid development of Convolutional Neural Networks (CNNs) in recent years has triggered significant breakthroughs in many machine learning (ML) applications. The ability to und…