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20182026
most citedKeeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

91 citations · 211 across the 29 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.SE2025

XBIDetective: Leveraging Vision Language Models for Identifying Cross-Browser Visual Inconsistencies

Balreet Grewal, James Graham, Jeff Muizelaar +4

Browser rendering bugs can be challenging to detect for browser developers, as they may be triggered by very specific conditions that are exhibited on only a very small subset of w…

cs.SE2025

Automated Bug Frame Retrieval from Gameplay Videos Using Vision-Language Models

Wentao Lu, Alexander Senchenko, Abram Hindle +1

Modern game studios deliver new builds and patches at a rapid pace, generating thousands of bug reports, many of which embed gameplay videos. To verify and triage these bug reports…

cs.CV2025

VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance

Mohammad Reza Taesiri, Abhijay Ghildyal, Saman Zadtootaghaj +2

With video games now generating the highest revenues in the entertainment industry, optimizing game development workflows has become essential for the sector's sustained growth. Re…

cs.SE2025★ 3 cited

A Systematic Literature Review of Software Engineering Research on Jupyter Notebook

Md Saeed Siddik, Hao Li, Cor-Paul Bezemer

Context: Jupyter Notebook has emerged as a versatile tool that transforms how researchers, developers, and data scientists conduct and communicate their work. As the adoption of Ju…

cs.SE2025

Exploring the Capabilities of Vision-Language Models to Detect Visual Bugs in HTML5 <canvas> Applications

Finlay Macklon, Cor-Paul Bezemer

The HyperText Markup Language 5 (HTML5) <canvas> is useful for creating visual-centric web applications. However, unlike traditional web applications, HTML5 <canvas> applications r…