papers

Publications (7)

cs.HC2023

Towards an Understanding and Explanation for Mixed-Initiative Artificial Scientific Text Detection

Luoxuan Weng, Minfeng Zhu, Kam Kwai Wong +5

Large language models (LLMs) have gained popularity in various fields for their exceptional capability of generating human-like text. Their potential misuse has raised social conce…

cs.HC2023

FraudAuditor: A Visual Analytics Approach for Collusive Fraud in Health Insurance

Jiehui Zhou, Xumeng Wang, Jie Wang +7

Collusive fraud, in which multiple fraudsters collude to defraud health insurance funds, threatens the operation of the healthcare system. However, existing statistical and machine…

cs.CV2026

Chart-FR1: Visual Focus-Driven Fine-Grained Reasoning on Dense Charts

Hongkun Pan, Yuwei Wu, Wanyi Hong +8

Multimodal large language models (MLLMs) have shown considerable potential in chart understanding and reasoning tasks. However, they still struggle with high information density (H…

cs.HC2020

GraphFederator: Federated Visual Analysis for Multi-party Graphs

Dongming Han, Wei Chen, Rusheng Pan +8

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs. Inspired by…

cs.SE2026

SGCR: A Specification-Grounded Framework for Trustworthy LLM Code Review

Kai Wang, Bingcheng Mao, Shuai Jia +4

Automating code review with Large Language Models (LLMs) shows immense promise, yet practical adoption is hampered by their lack of reliability, context-awareness, and control. To…

quant-ph2023

Quantivine: A Visualization Approach for Large-scale Quantum Circuit Representation and Analysis

Zhen Wen, Yihan Liu, Siwei Tan +6

Quantum computing is a rapidly evolving field that enables exponential speed-up over classical algorithms. At the heart of this revolutionary technology are quantum circuits, which…

cs.CL2023

Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Prediction

Yujie Ding, Shuai Jia, Tianyi Ma +4

The remarkable achievements and rapid advancements of Large Language Models (LLMs) such as ChatGPT and GPT-4 have showcased their immense potential in quantitative investment. Trad…