14 citations · 17 across the 27 of their papers we have counts for
27 papers
Does It Render Everywhere? A Study of Cross-Environment Compatibility in MLLM-Generated Webpages
Ziyun Guo, Jingyu Xiao, Yuqiang Sun +1
Multimodal Large Language Models (MLLMs) have been increasingly adopted to automate webpage generation from visual designs (e.g., screenshots). However, existing evaluations are li…
Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents
Junliang Liu, Ruoyu Li, Wenxin Tang +4
LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progressive-disclosure design expose…
CodeShrink: Adaptive Visual Compression for Efficient Multimodal Code Understanding
Wenxin Tang, Jingyu Xiao, Zhenyu Liu +6
Rendering source code as images offers a promising way to reduce the input costs of Multimodal Large Language Models (MLLMs). Adjusting image resolution can trade visual token cost…
VisualRepair: Dynamic Tool Calling and Region Focusing for Visual Software Issue Repair
Jingyu Xiao, Zhongyi Zhang, Haoran Hou +4
Automated Program Repair (APR) has witnessed significant progress with the advent of Large Language Models (LLMs). However, as modern software systems increasingly expose rich grap…
Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence
Xuanle Zhao, Qiushi Sun, Jingyu Xiao +16
While Large Language Models (LLMs) have substantially advanced text-to-code generation, many real programming tasks specify intent through visual artifacts such as screenshots, cha…
From Runnable to Shippable: Multi-Agent Test-Driven Development for Generating Full-Stack Web Applications from Requirements
Yuxuan Wan, Tingshuo Liang, Jiakai Xu +3
Coding agents can generate runnable web applications, but their outputs frequently fail to satisfy functional requirements. Although test-driven development (TDD) offers a principl…
SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades
Man Ho Lam, Chaozheng Wang, Hange Liu +5
Coding agents powered by large language models are increasingly expected to perform realistic software maintenance tasks beyond isolated issue resolution. Existing benchmarks have…
UIBenchKit: A unified toolkit for design-to-code model evaluation
Chinh T. Le, Trevor Ong Yee Siang, Jingyu Xiao +2
Recent years have seen substantial progress in automated design-to-code generation, with many methods proposed for generating HTML and CSS from webpage screenshots. However, the ab…
VulTriage: Triple-Path Context Augmentation for LLM-Based Vulnerability Detection
Wenxin Tang, Xiang Zhang, Junliang Liu +11
Automated vulnerability detection is a fundamental task in software security, yet existing learning-based methods still struggle to capture the structural dependencies, domain-spec…
DCVD: Dual-Channel Cross-Modal Fusion for Joint Vulnerability Detection and Localization
Wenxin Tang, Wenbin Li, Junliang Liu +10
Software vulnerability detection plays a critical role in ensuring system security, where real-world auditing requires not only determining whether a function is vulnerable but als…
ST-Lite: Training-Free KV Cache Compression with Spatio-Trajectory Guidance for Long-Horizon GUI Agents
Bowen Zhou, Zhou Xu, Wanli Li +3
Training-free KV cache compression is essential for deploying vision-language GUI agents under memory and latency constraints, yet existing methods are designed for generic languag…
Spatio-Temporal Token Pruning for Efficient High-Resolution GUI Agents
Zhou Xu, Bowen Zhou, Qi Wang +2
Pure-vision GUI agents provide universal interaction capabilities but suffer from severe efficiency bottlenecks due to the massive spatiotemporal redundancy inherent in high-resolu…
EfficientPosterGen: Semantic-aware Efficient Poster Generation via Token Compression and Accurate Violation Detection
Wenxin Tang, Jingyu Xiao, Yanpei Gong +6
Automated academic poster generation aims to distill lengthy research papers into concise, visually coherent presentations. Existing Multimodal Large Language Models (MLLMs) based…
ComUICoder: Component-based Reusable UI Code Generation for Complex Websites via Semantic Segmentation and Element-wise Feedback
Jingyu Xiao, Jiantong Qin, Shuoqi Li +5
Multimodal Large Language Models (MLLMs) have demonstrated strong performance on the UI-to-code task, which aims to generate UI code from design mock-ups. However, when applied to…
Motion-Aware Vision-Reference Alignment for Referring Multi-Object Tracking
Weiyi Lv, Ning Zhang, Hanyang Sun +5
Referring Multi-Object Tracking (RMOT) extends conventional multi-object tracking (MOT) by introducing natural language references for multi-modal fusion tracking. RMOT benchmarks…
Envisioning Future Interactive Web Development: Editing Webpage with Natural Language
Truong Hai Dang, Jingyu Xiao, Yintong Huo
The evolution of web applications relies on iterative code modifications, a process that is traditionally manual and time-consuming. While Large Language Models (LLMs) can generate…
TREAT: A Code LLMs Trustworthiness / Reliability Evaluation and Testing Framework
Shuzheng Gao, Eric John Li, Man Ho Lam +5
Large foundation models are fundamentally transforming the software engineering landscape, demonstrating exceptional capabilities across diverse tasks such as code generation, debu…
Automatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development
Yuxuan Wan, Tingshuo Liang, Jiakai Xu +3
Developing full-stack web applications is complex and time-intensive, demanding proficiency across diverse technologies and frameworks. Although recent advances in multimodal large…
Benchmarking MLLM-based Web Understanding: Reasoning, Robustness and Safety
Junliang Liu, Jingyu Xiao, Wenxin Tang +5
Multimodal large language models (MLLMs) are increasingly deployed as the core reasoning engine for web-facing systems, powering GUI agents and front-end automation that must inter…
EfficientUICoder: A Bidirectional Token Compression Framework for Efficient MLLM-Based UI Code Generation
Jingyu Xiao, Zhongyi Zhang, Yuxuan Wan +3
Multimodal Large Language Models have demonstrated exceptional performance in UI2Code tasks, significantly enhancing website development efficiency. However, these tasks incur subs…
SlideCoder: Layout-aware RAG-enhanced Hierarchical Slide Generation from Design
Wenxin Tang, Jingyu Xiao, Wenxuan Jiang +8
Manual slide creation is labor-intensive and requires expert prior knowledge. Existing natural language-based LLM generation methods struggle to capture the visual and structural n…
Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models
Chengyue Huang, Yuchen Zhu, Sichen Zhu +4
Vision-language models (VLMs) are widely assumed to exhibit in-context learning (ICL), a property similar to that of their language-only counterparts. While recent work suggests VL…
DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation
Jingyu Xiao, Ming Wang, Man Ho Lam +4
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in automated front-end engineering, e.g., generating UI code from visual designs. However, existi…
Enhancing the Non-Functional Quality Compliance of LLM-Generated Code through Quality-Aware Preference Learning
Liang Lu, Yuan Jiang, Christoph Treude +4
Large Language Models (LLMs) have been widely adopted in commercial code completion engines, significantly enhancing coding efficiency and productivity. However, even functionally…