EvolvingLMMs-Lab/lmms-eval
Oct 2024 – Jul 2026
20 Months active
Languages Used
MarkdownPythonYAMLShellJinjabash
Technical Skills
DocumentationMachine LearningModel IntegrationVideo ProcessingAPI IntegrationAudio Processing
kcz358
PROFILE
Kcz358
Over 20 months, contributed to the EvolvingLMMs-Lab/lmms-eval repository by building and refining a comprehensive evaluation framework for multimodal AI models. Developed features supporting video, audio, and image processing, including robust benchmarking tools for tasks such as OCR, grounding, and temporal grounding in videos. Leveraged Python, YAML, and PyTorch to implement scalable data pipelines, REST APIs, and automated evaluation endpoints. Addressed reliability through targeted bug fixes, code refactoring, and enhanced error handling. Improved developer experience with clear documentation and streamlined onboarding. The work enabled reproducible, cross-benchmark model evaluation, supporting both research and production use cases in machine learning.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
80Total
Bugs
19
Commits
80
Features
38
Lines of code
323,240
Activity Months20
Your Network
95 peopleWork History
July 2026
8 Commits • 6 Features
Jul 1, 2026July 2026 performance: Expanded the lmms-eval evaluation framework with major feature deliveries across OCR benchmarking, grounding, zero-shot detection, 3D detection, and video/object segmentation benchmarks; introduced robust data handling, serialization, and submission pipelines to support scalable, reproducible evaluations; and addressed reliability gaps via targeted fixes. This expanded coverage enables faster, data-driven model iteration and more trustworthy business decisions around model selection and deployment readiness.
8 Commits • 6 Features
Jul 1, 2026July 2026 performance: Expanded the lmms-eval evaluation framework with major feature deliveries across OCR benchmarking, grounding, zero-shot detection, 3D detection, and video/object segmentation benchmarks; introduced robust data handling, serialization, and submission pipelines to support scalable, reproducible evaluations; and addressed reliability gaps via targeted fixes. This expanded coverage enables faster, data-driven model iteration and more trustworthy business decisions around model selection and deployment readiness.
July 2026
June 2026
3 Commits • 2 Features
Jun 1, 2026June 2026 highlights: Delivered multi-round chat support in OVO-Bench with enhanced data loading and auto-download of chunked videos; fixed multi-round output processing to preserve list-based outputs and improved evaluation reliability; expanded ChartQAPro evaluation tooling with cross-benchmark fixes for MMT and ScreenSpot; achieved code quality gains with automated linting and safer data handling. These changes reduced manual data prep, improved usability, and enabled more scalable and trustworthy model benchmarking.
June 2026
3 Commits • 2 Features
Jun 1, 2026June 2026 highlights: Delivered multi-round chat support in OVO-Bench with enhanced data loading and auto-download of chunked videos; fixed multi-round output processing to preserve list-based outputs and improved evaluation reliability; expanded ChartQAPro evaluation tooling with cross-benchmark fixes for MMT and ScreenSpot; achieved code quality gains with automated linting and safer data handling. These changes reduced manual data prep, improved usability, and enabled more scalable and trustworthy model benchmarking.
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focused on delivering a robust evaluation capability for Timelens temporal grounding tasks. Key feature delivered: Timelens Evaluation Benchmark and IOU Metrics, introducing a benchmark for Timelens, multiple IOU metrics, and utility functions to process results to enable improved evaluation of temporal grounding in videos. This work is anchored by the primary change committed in the period: 26f1d8e3692a5985e728e79510eb0faad798a358 (feat: add timelens benchmark (#1323)). No major bugs fixed this month. Impact: provides a rigorous, repeatable evaluation protocol that informs model development, enabling clearer measurement of improvements in temporal grounding. Technologies/skills demonstrated: Python-based benchmarks, IOU metric implementations, data processing utilities, and collaboration through commit-based workflows.
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focused on delivering a robust evaluation capability for Timelens temporal grounding tasks. Key feature delivered: Timelens Evaluation Benchmark and IOU Metrics, introducing a benchmark for Timelens, multiple IOU metrics, and utility functions to process results to enable improved evaluation of temporal grounding in videos. This work is anchored by the primary change committed in the period: 26f1d8e3692a5985e728e79510eb0faad798a358 (feat: add timelens benchmark (#1323)). No major bugs fixed this month. Impact: provides a rigorous, repeatable evaluation protocol that informs model development, enabling clearer measurement of improvements in temporal grounding. Technologies/skills demonstrated: Python-based benchmarks, IOU metric implementations, data processing utilities, and collaboration through commit-based workflows.
May 2026
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focusing on feature delivery, maintenance work, impact, and skills demonstrated.
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focusing on feature delivery, maintenance work, impact, and skills demonstrated.
March 2026
1 Commits
Mar 1, 2026March 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval: Delivered a critical bug fix and improvements to video metadata propagation in the Qwen2.5 VL path. The changes improve temporal encoding accuracy and data integrity for sampled videos, achieving cross-version parity with Qwen3 VL and reducing downstream errors in the video processing pipeline.
1 Commits
Mar 1, 2026March 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval: Delivered a critical bug fix and improvements to video metadata propagation in the Qwen2.5 VL path. The changes improve temporal encoding accuracy and data integrity for sampled videos, achieving cross-version parity with Qwen3 VL and reducing downstream errors in the video processing pipeline.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focused on documentation improvements for the HTTP Evaluation Server and custom model integration. Enhanced user onboarding, reduced ambiguity in integration steps, and improved maintainability of the evaluation tooling docs.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focused on documentation improvements for the HTTP Evaluation Server and custom model integration. Enhanced user onboarding, reduced ambiguity in integration steps, and improved maintainability of the evaluation tooling docs.
January 2026
5 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval: Delivered a scalable evaluation framework for visual reasoning with automated evaluation endpoints, expanded task coverage, and improved evaluation accuracy. Focused on automation, reproducibility, and cross-benchmark support to accelerate iteration and produce more reliable results for researchers and product teams.
5 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval: Delivered a scalable evaluation framework for visual reasoning with automated evaluation endpoints, expanded task coverage, and improved evaluation accuracy. Focused on automation, reproducibility, and cross-benchmark support to accelerate iteration and produce more reliable results for researchers and product teams.
January 2026
December 2025
5 Commits • 3 Features
Dec 1, 2025Concise monthly summary for 2025-12 focused on delivering tangible business value through robust evaluation tools, improved user feedback during batch inference, and expanded image-text generation capabilities. The LMMS-Eval project advanced its ability to measure reasoning performance, streamline generation pipelines, and benchmark image editing tasks within Vision-Language workflows.
December 2025
5 Commits • 3 Features
Dec 1, 2025Concise monthly summary for 2025-12 focused on delivering tangible business value through robust evaluation tools, improved user feedback during batch inference, and expanded image-text generation capabilities. The LMMS-Eval project advanced its ability to measure reasoning performance, streamline generation pipelines, and benchmark image editing tasks within Vision-Language workflows.
November 2025
3 Commits • 2 Features
Nov 1, 2025November 2025 at EvolvingLMMs-Lab focused on delivering interactive visual chat capabilities, fortifying visual data processing reliability, and improving developer onboarding. The month delivered a new end-to-end visual chat capability, enhanced robustness for LongVila embeddings and visual-to-document mapping, and streamlined setup guidance to accelerate team onboarding and reproducibility. Business value was realized through increased user engagement with multimodal interactions, more reliable visual data workflows, and faster installation with clear setup documentation.
3 Commits • 2 Features
Nov 1, 2025November 2025 at EvolvingLMMs-Lab focused on delivering interactive visual chat capabilities, fortifying visual data processing reliability, and improving developer onboarding. The month delivered a new end-to-end visual chat capability, enhanced robustness for LongVila embeddings and visual-to-document mapping, and streamlined setup guidance to accelerate team onboarding and reproducibility. Business value was realized through increased user engagement with multimodal interactions, more reliable visual data workflows, and faster installation with clear setup documentation.
November 2025
October 2025
7 Commits • 2 Features
Oct 1, 2025Concise monthly summary for 2025-10: Deliveries centered on multimodal inference improvements, robust async OpenAI integration, and evaluation tooling refinements for lmms-eval. Key results include strengthened video processing pipelines, reliable asynchronous model calls, and clarified evaluation model references, enabling faster iteration and more trustworthy comparisons.
October 2025
7 Commits • 2 Features
Oct 1, 2025Concise monthly summary for 2025-10: Deliveries centered on multimodal inference improvements, robust async OpenAI integration, and evaluation tooling refinements for lmms-eval. Key results include strengthened video processing pipelines, reliable asynchronous model calls, and clarified evaluation model references, enabling faster iteration and more trustworthy comparisons.
September 2025
10 Commits • 3 Features
Sep 1, 2025September 2025: Key features delivered include multimedia support in OpenAI chat, a robust caching layer for model evaluations and API calls, and LongVila-R1 model support with LVBench integration. Production stability improved by removing a debugging breakpoint in the chat flow. Impact: lower latency, reduced API costs, broader multimodal evaluation capabilities, and improved reliability. Technologies demonstrated: caching architecture, per-class hashing, vLLM caching, robust media handling, and multimodal model support.
10 Commits • 3 Features
Sep 1, 2025September 2025: Key features delivered include multimedia support in OpenAI chat, a robust caching layer for model evaluations and API calls, and LongVila-R1 model support with LVBench integration. Production stability improved by removing a debugging breakpoint in the chat flow. Impact: lower latency, reduced API costs, broader multimodal evaluation capabilities, and improved reliability. Technologies demonstrated: caching architecture, per-class hashing, vLLM caching, robust media handling, and multimodal model support.
September 2025
August 2025
9 Commits • 3 Features
Aug 1, 2025August 2025 performance review: The team delivered significant features across video multimodal processing and evaluation tooling, improved model telemetry and initialization, and fixed critical data/config and batch-processing bugs. These efforts improved evaluation accuracy, inference reliability, and maintainability, delivering clear business value in faster, more trustworthy model evaluation and deployment workflows.
August 2025
9 Commits • 3 Features
Aug 1, 2025August 2025 performance review: The team delivered significant features across video multimodal processing and evaluation tooling, improved model telemetry and initialization, and fixed critical data/config and batch-processing bugs. These efforts improved evaluation accuracy, inference reliability, and maintainability, delivering clear business value in faster, more trustworthy model evaluation and deployment workflows.
July 2025
1 Commits
Jul 1, 2025July 2025: Focused on stability and reliability in lmms-eval by reverting a caching tweak that passed cache_dir to snapshot_download, restoring default caching behavior. This change reduces user confusion, prevents cache fragmentation, and improves reproducibility across environments. The work underscores a commitment to backward compatibility and predictable performance for users.
1 Commits
Jul 1, 2025July 2025: Focused on stability and reliability in lmms-eval by reverting a caching tweak that passed cache_dir to snapshot_download, restoring default caching behavior. This change reduces user confusion, prevents cache fragmentation, and improves reproducibility across environments. The work underscores a commitment to backward compatibility and predictable performance for users.
July 2025
June 2025
1 Commits
Jun 1, 2025June 2025: Monthly summary for EvolvingLMMs-Lab/lmms-eval focused on stabilization of configuration and sampling, addressing warnings, and broadening compatibility. Delivered a bug fix that stabilizes sampling behavior based on temperature, removes redundant YAML group configurations, and expands minimum Python version support, as captured in commit 9935012ad76f8c4c2b0f37f8843664b2cb27e3c2 (#704).
June 2025
1 Commits
Jun 1, 2025June 2025: Monthly summary for EvolvingLMMs-Lab/lmms-eval focused on stabilization of configuration and sampling, addressing warnings, and broadening compatibility. Delivered a bug fix that stabilizes sampling behavior based on temperature, removes redundant YAML group configurations, and expands minimum Python version support, as captured in commit 9935012ad76f8c4c2b0f37f8843664b2cb27e3c2 (#704).
April 2025
4 Commits • 4 Features
Apr 1, 2025April 2025 performance summary for repo EvolvingLMMs-Lab/lmms-eval: Focused on extending long-form transcription capabilities, enabling processing of longer audio inputs, and strengthening model initialization/evaluation workflows. Delivered a new Aero-1-Audio integration to broaden the framework's audio generation capabilities. These efforts improved use-case coverage, reliability, and developer experience, delivering measurable business value in scalability and accuracy.
4 Commits • 4 Features
Apr 1, 2025April 2025 performance summary for repo EvolvingLMMs-Lab/lmms-eval: Focused on extending long-form transcription capabilities, enabling processing of longer audio inputs, and strengthening model initialization/evaluation workflows. Delivered a new Aero-1-Audio integration to broaden the framework's audio generation capabilities. These efforts improved use-case coverage, reliability, and developer experience, delivering measurable business value in scalability and accuracy.
April 2025
March 2025
3 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for EvolvingLMMs-Lab/lmms-eval: Key fixes and new evaluation capabilities expanded reliability and scope, enabling broader research on multimodal and ASR tasks within the framework.
March 2025
3 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for EvolvingLMMs-Lab/lmms-eval: Key fixes and new evaluation capabilities expanded reliability and scope, enabling broader research on multimodal and ASR tasks within the framework.
February 2025
7 Commits • 2 Features
Feb 1, 2025February 2025: lmms-eval contributions focused on expanding dataset support, stabilizing data processing, and integrating multimodal evaluation capabilities. Delivered FLEURS support with English and Chinese splits, integrated VITA 1.5, and hardened dataset handling for Common Voice and MMMU documentation-to-text robustness.
7 Commits • 2 Features
Feb 1, 2025February 2025: lmms-eval contributions focused on expanding dataset support, stabilizing data processing, and integrating multimodal evaluation capabilities. Delivered FLEURS support with English and Chinese splits, integrated VITA 1.5, and hardened dataset handling for Common Voice and MMMU documentation-to-text robustness.
February 2025
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly performance summary for EvolvingLMMs-Lab/lmms-eval, focusing on feature delivery, reliability improvements, and business impact.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly performance summary for EvolvingLMMs-Lab/lmms-eval, focusing on feature delivery, reliability improvements, and business impact.
November 2024
5 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for EvolvingLMMs-Lab/lmms-eval: Focused on stabilizing and expanding multimodal evaluation capabilities to deliver tangible business value. Key milestones include robust fixes across the LMMS-eval evaluation framework (Qwen2_VL output processing, ANLS aggregation, multiple target handling, end-of-text generation, and log-likelihood calculation accuracy) with commits b5c99bc2728bcbc668b0e48ffcf0748cdd3ec51 and e88389dc6ac012c962a42a0a2ffcf58d772029e4; a cleanup of the Hallusion benchmark document structure by removing an image field to prevent processing errors (#392); enabling video processing in Idefics2 (video loading and frame extraction) (#418); and the release of LMMS-eval v0.3.0 introducing audio evaluation support with new models (Qwen2-Audio, Gemini-Audio) and tasks (ASR, Audio Instruction Following) across LibriSpeech, Clotho-AQA, and GigaSpeech (#428). These contributions extend evaluation coverage to video and audio modalities, improve result reliability, and accelerate how teams measure model capabilities, delivering clearer business value and faster iteration.
5 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for EvolvingLMMs-Lab/lmms-eval: Focused on stabilizing and expanding multimodal evaluation capabilities to deliver tangible business value. Key milestones include robust fixes across the LMMS-eval evaluation framework (Qwen2_VL output processing, ANLS aggregation, multiple target handling, end-of-text generation, and log-likelihood calculation accuracy) with commits b5c99bc2728bcbc668b0e48ffcf0748cdd3ec51 and e88389dc6ac012c962a42a0a2ffcf58d772029e4; a cleanup of the Hallusion benchmark document structure by removing an image field to prevent processing errors (#392); enabling video processing in Idefics2 (video loading and frame extraction) (#418); and the release of LMMS-eval v0.3.0 introducing audio evaluation support with new models (Qwen2-Audio, Gemini-Audio) and tasks (ASR, Audio Instruction Following) across LibriSpeech, Clotho-AQA, and GigaSpeech (#428). These contributions extend evaluation coverage to video and audio modalities, improve result reliability, and accelerate how teams measure model capabilities, delivering clearer business value and faster iteration.
November 2024
October 2024
3 Commits • 2 Features
Oct 1, 2024October 2024 monthly summary for EvolvingLMMs-Lab/lmms-eval: Focused on delivering configurable video input for Qwen2-VL, enabling precise resource usage and scalable processing, along with documentation updates to improve benchmarking visibility and citation traceability. No major bug fixes recorded in this period.
October 2024
3 Commits • 2 Features
Oct 1, 2024October 2024 monthly summary for EvolvingLMMs-Lab/lmms-eval: Focused on delivering configurable video input for Qwen2-VL, enabling precise resource usage and scalable processing, along with documentation updates to improve benchmarking visibility and citation traceability. No major bug fixes recorded in this period.
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Quality Metrics
Correctness89.2%
Maintainability85.2%
Architecture86.6%
Performance80.0%
AI Usage36.8%
Skills & Technologies
Programming Languages
JinjaMarkdownPythonShellYAMLbash
Technical Skills
AI DevelopmentAI EvaluationAI IntegrationAI Model EvaluationAPI DevelopmentAPI IntegrationAPI developmentAPI integrationAsynchronous ProgrammingAudio ProcessingBackend DevelopmentBatch ProcessingBenchmarkingBug FixBug Fixing
Repositories Contributed To
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