embeddings-benchmark/mteb
Apr 2026 – Apr 2026
1 Month active
Languages Used
Python
Technical Skills
Audio ProcessingData ProcessingMachine LearningPythonVideo Processingcode formatting
AdnanElAssadi
PROFILE
Adnanelassadi
Worked on the embeddings-benchmark/mteb repository to enhance media processing capabilities within the LCOEmbedding module, focusing on both video and audio data. Integrated VideoCollator and AudioCollator components, enabling robust handling of diverse media types and improving the fidelity of benchmarking workflows. Replaced a legacy dependency with direct processor calls, reducing runtime brittleness and streamlining the processing pipeline. Introduced configurable parameters for frame rate and audio length, as well as L2 normalization to ensure consistent embedding scales. Applied Python-based code formatting and linting practices, resulting in improved readability and maintainability. Demonstrated skills in audio processing, video processing, and machine learning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
175
Activity Months1
Your Network
120 peopleSame Organization
@ku.edu.tr3
Work History
April 2026
2 Commits • 2 Features
Apr 1, 2026April 2026 (2026-04) monthly summary for embeddings-benchmark/mteb: Delivered enhancements to LCOEmbedding media processing and improved code quality, driving reliability, configurability, and maintainability for benchmarking workflows.
2 Commits • 2 Features
Apr 1, 2026April 2026 (2026-04) monthly summary for embeddings-benchmark/mteb: Delivered enhancements to LCOEmbedding media processing and improved code quality, driving reliability, configurability, and maintainability for benchmarking workflows.
April 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Audio ProcessingData ProcessingMachine LearningPythonVideo Processingcode formattinglinting
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