124 citations · 301 across the 32 of their papers we have counts for
32 papers
ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL
Zhaorui Yang, Huawei Zheng, Sen Yang +14
Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world databases often contain large…
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…
InterDeepResearch: Enabling Human-Agent Collaborative Information Seeking through Interactive Deep Research
Bo Pan, Lunke Pan, Yitao Zhou +4
Deep research systems powered by LLM agents have transformed complex information seeking by automating the iterative retrieval, filtering, and synthesis of insights from massive-sc…
RAGExplorer: A Visual Analytics System for the Comparative Diagnosis of RAG Systems
Haoyu Tian, Yingchaojie Feng, Zhen Wen +3
The advent of Retrieval-Augmented Generation (RAG) has significantly enhanced the ability of Large Language Models (LLMs) to produce factually accurate and up-to-date responses. Ho…
V-Zero: Self-Improving Multimodal Reasoning with Zero Annotation
Han Wang, Yi Yang, Jingyuan Hu +2
Recent advances in multimodal learning have significantly enhanced the reasoning capabilities of vision-language models (VLMs). However, state-of-the-art approaches rely heavily on…
IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation
Yinghao Tang, Xueding Liu, Boyuan Zhang +13
Infographics are composite visual artifacts that combine data visualizations with textual and illustrative elements to communicate information. While recent text-to-image (T2I) mod…
ConceptViz: A Visual Analytics Approach for Exploring Concepts in Large Language Models
Haoxuan Li, Zhen Wen, Qiqi Jiang +7
Large language models (LLMs) have achieved remarkable performance across a wide range of natural language tasks. Understanding how LLMs internally represent knowledge remains a sig…
GenesisGeo: Technical Report
Minfeng Zhu, Zi Wang, Sizhe Ji +8
Recent neuro-symbolic geometry theorem provers have made significant progress on Euclidean problems by coupling neural guidance with symbolic verification. However, most existing s…
VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation
Bo Pan, Yixiao Fu, Ke Wang +15
Data visualization generation using Large Language Models (LLMs) has shown promising results but often produces suboptimal visualizations that require human intervention for improv…
XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
Ke Wang, Bo Pan, Yingchaojie Feng +4
Graph-based Retrieval-Augmented Generation (RAG) has shown great capability in enhancing Large Language Model (LLM)'s answer with an external knowledge base. Compared to traditiona…
IntuiTF: MLLM-Guided Transfer Function Optimization for Direct Volume Rendering
Yiyao Wang, Bo Pan, Ke Wang +8
Direct volume rendering (DVR) is a fundamental technique for visualizing volumetric data, where transfer functions (TFs) play a crucial role in extracting meaningful structures. Ho…
Multimodal DeepResearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework
Zhaorui Yang, Bo Pan, Han Wang +8
Visualizations play a crucial part in effective communication of concepts and information. Recent advances in reasoning and retrieval augmented generation have enabled Large Langua…
Don't Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation
Yingchaojie Feng, Yiqun Sun, Yandong Sun +4
In this work, we investigate an important task named instruction-following text embedding, which generates dynamic text embeddings that adapt to user instructions, highlighting spe…
Exploring Multimodal Prompt for Visualization Authoring with Large Language Models
Zhen Wen, Luoxuan Weng, Yinghao Tang +5
Recent advances in large language models (LLMs) have shown great potential in automating the process of visualization authoring through simple natural language utterances. However,…
R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
Yi Yang, Xiaoxuan He, Hongkun Pan +9
Large Language Models have demonstrated remarkable reasoning capability in complex textual tasks. However, multimodal reasoning, which requires integrating visual and textual infor…
DataLab: A Unified Platform for LLM-Powered Business Intelligence
Luoxuan Weng, Yinghao Tang, Yingchaojie Feng +18
Business intelligence (BI) transforms large volumes of data within modern organizations into actionable insights for informed decision-making. Recently, large language model (LLM)-…
MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model
Xinyang Wang, Yi Yang, Minfeng Zhu +3
Recent advancements in pre-trained Vision-Language Models (VLMs) have highlighted the significant potential of prompt tuning for adapting these models to a wide range of downstream…
CultiVerse: Towards Cross-Cultural Understanding for Paintings with Large Language Model
Wei Zhang, Wong Kam-Kwai, Biying Xu +5
The integration of new technology with cultural studies enhances our understanding of cultural heritage but often struggles to connect with diverse audiences. It is challenging to…
AgentCoord: Visually Exploring Coordination Strategy for LLM-based Multi-Agent Collaboration
Bo Pan, Jiaying Lu, Ke Wang +5
The potential of automatic task-solving through Large Language Model (LLM)-based multi-agent collaboration has recently garnered widespread attention from both the research communi…
JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
Yingchaojie Feng, Zhizhang Chen, Zhining Kang +5
The proliferation of large language models (LLMs) has underscored concerns regarding their security vulnerabilities, notably against jailbreak attacks, where adversaries design jai…
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
Zhaorui Yang, Tianyu Pang, Haozhe Feng +4
The surge in Large Language Models (LLMs) has revolutionized natural language processing, but fine-tuning them for specific tasks often encounters challenges in balancing performan…
PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation
Yingchaojie Feng, Xingbo Wang, Kam Kwai Wong +5
Generative text-to-image models have gained great popularity among the public for their powerful capability to generate high-quality images based on natural language prompts. Howev…
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…
CoSDA: Continual Source-Free Domain Adaptation
Haozhe Feng, Zhaorui Yang, Hesun Chen +5
Without access to the source data, source-free domain adaptation (SFDA) transfers knowledge from a source-domain trained model to target domains. Recently, SFDA has gained populari…