EvolvingLMMs-Lab/lmms-eval
Dec 2025 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
API developmentdata validationmachine learningvideo processingAPI DevelopmentCLI development
Zuhao Yang
PROFILE
Zuhao Yang
Zuhao developed advanced video evaluation and analysis features for the EvolvingLMMs-Lab/lmms-eval repository, focusing on long-form video understanding and robust benchmarking. He implemented a Python-based cropping and evaluation tool that automated end-to-end processing of lengthy video data, reducing manual intervention and expanding analytical coverage. His work introduced configurable decontamination settings, enhanced statistical evaluation metrics using clustered standard errors and CLT-based methods, and integrated baseline testing with paired t-tests. By adding the BabyVision multimodal visual reasoning benchmark and pre-evaluation power analysis, Zuhao enabled more reliable, extensible model evaluation workflows, demonstrating depth in data processing, statistical modeling, and API development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
5
Lines of code
3,045
Activity Months2
Your Network
99 peopleSame Organization
@ualberta.ca18
Work History
January 2026
5 Commits • 4 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for EvolvingLMMs-Lab/lmms-eval. This period focused on delivering advanced evaluation capabilities, flexible benchmarking configurations, and the groundwork for data-driven planning. Key features delivered include configurable video benchmark decontamination settings, enhanced statistical evaluation metrics (clustered standard errors, CLT-based metrics) with baseline testing via paired t-tests, the BabyVision multimodal visual reasoning benchmark with task configuration and API integration, and pre-evaluation power analysis for minimum sample size in paired t-tests. No major bugs were reported this month; the work emphasized robustness, extensibility, and actionable insights. Technologies demonstrated include statistical rigor (CLT, clustered SE, t-tests), multimodal benchmarking, environment-variable based API integration, and planning-oriented tooling for resource estimation, contributing to faster, more reliable model evaluation and better resource planning.
5 Commits • 4 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for EvolvingLMMs-Lab/lmms-eval. This period focused on delivering advanced evaluation capabilities, flexible benchmarking configurations, and the groundwork for data-driven planning. Key features delivered include configurable video benchmark decontamination settings, enhanced statistical evaluation metrics (clustered standard errors, CLT-based metrics) with baseline testing via paired t-tests, the BabyVision multimodal visual reasoning benchmark with task configuration and API integration, and pre-evaluation power analysis for minimum sample size in paired t-tests. No major bugs were reported this month; the work emphasized robustness, extensibility, and actionable insights. Technologies demonstrated include statistical rigor (CLT, clustered SE, t-tests), multimodal benchmarking, environment-variable based API integration, and planning-oriented tooling for resource estimation, contributing to faster, more reliable model evaluation and better resource planning.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Key feature delivered in lmms-eval: Long Video Cropping and Evaluation Tool (LongVT) for long-video understanding, with tool-calling support. Introduced a cropping workflow and evaluation tasks to enable end-to-end processing of long-form video data and deeper insights. No major bugs fixed in this repo this month. Impact: expands the framework’s long-video processing capabilities, reduces manual preprocessing, and improves evaluation coverage for long-form content. Technologies/skills demonstrated: Python-based tooling, tool-calling integration, video processing pipeline, evaluation framework, and strong commit traceability (b0da65de53bfa6fd52010b7d1a86dfd2f598764c).
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Key feature delivered in lmms-eval: Long Video Cropping and Evaluation Tool (LongVT) for long-video understanding, with tool-calling support. Introduced a cropping workflow and evaluation tasks to enable end-to-end processing of long-form video data and deeper insights. No major bugs fixed in this repo this month. Impact: expands the framework’s long-video processing capabilities, reduces manual preprocessing, and improves evaluation coverage for long-form content. Technologies/skills demonstrated: Python-based tooling, tool-calling integration, video processing pipeline, evaluation framework, and strong commit traceability (b0da65de53bfa6fd52010b7d1a86dfd2f598764c).
Activity
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Quality Metrics
Correctness96.6%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API DevelopmentAPI developmentCLI developmentData ProcessingMachine LearningNatural Language ProcessingPythonPython programmingVideo Analysiscommand line interface (CLI) developmentdata analysisdata processingdata validationmachine learningsoftware development
Repositories Contributed To
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