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Ardalan

PROFILE

Ardalan

Contributed to EvolvingLMMs-Lab/lmms-eval and liguodongiot/transformers by building and refining multimodal large language model evaluation tools and model integration pipelines. Developed features for image and video input processing, batch inference, and prompt system integration, focusing on runtime performance and alignment with official benchmarks. Addressed numerical stability and data type compatibility in DeepSpeed-enabled training for Qwen2VL, improving reliability for large-scale model deployment. Introduced a benchmarking framework for multimodal LLMs in social network contexts, supporting standardized evaluation. Worked primarily with Python and PyTorch, applying deep learning, computer vision, and natural language processing expertise to deliver robust, maintainable solutions.

Overall Statistics

Feature vs Bugs

83%Features

Repository Contributions

8Total
Bugs
1
Commits
8
Features
5
Lines of code
1,349
Activity Months3

Work History

December 2025

3 Commits • 3 Features

Dec 1, 2025

December 2025 monthly summary for the EvolvingLMMs-Lab/lmms-eval repository focused on performance refinements and evaluation tooling for multimodal LLMs. Delivered three primary features with measurable business impact, stabilized core data paths, and established a reusable benchmarking framework to accelerate future development and evaluation.

November 2025

4 Commits • 2 Features

Nov 1, 2025

Month 2025-11: Delivered key features for multimodal inference and configuration management in lmms-eval. Focused on Qwen3-VL integration with batch processing and alignment with official results, along with MMstar/OpenCompass config refactor. Implemented critical bug fixes to stabilize batch processing and video generation parity with VideoMME, contributing to reliable benchmarking and scalable deployment.

February 2025

1 Commits

Feb 1, 2025

February 2025 monthly work summary for liguodongiot/transformers. Focused on stabilizing DeepSpeed integration for Qwen2VL by fixing data type handling for cosine and sine functions to ensure compatibility with DeepSpeed, improving numerical stability and training performance.

Activity

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Quality Metrics

Correctness85.0%
Maintainability82.6%
Architecture82.6%
Performance82.6%
AI Usage60.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

AI model evaluationComputer VisionDeep LearningMachine LearningModel DeploymentNLPNatural Language ProcessingPyTorchPythonPython programmingdata analysisdata processingdeep learningimage processingmachine learning

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

EvolvingLMMs-Lab/lmms-eval

Nov 2025 Dec 2025
2 Months active

Languages Used

Python

Technical Skills

AI model evaluationComputer VisionDeep LearningMachine LearningModel DeploymentNatural Language Processing

liguodongiot/transformers

Feb 2025 Feb 2025
1 Month active

Languages Used

Python

Technical Skills

PyTorchdeep learningmodel optimizationnumerical stability