thunlp/SIR-Bench
Nov 2024 – Apr 2025
4 Months active
Languages Used
MarkdownPythonYAML
Technical Skills
Configuration ManagementData EngineeringData EvaluationData LoadingData ManagementDataset Handling
liushz
PROFILE
Liushz
Worked on the thunlp/SIR-Bench repository to expand and strengthen benchmarking capabilities for large language models, focusing on dataset integration, evaluation workflows, and configuration management. Over four months, delivered features such as loading and evaluating new datasets—including OlymMATH, HLE, AIME2025, and LiveStemBench—while enhancing data access, integrity, and reproducibility. Addressed configuration and parameter handling issues to ensure robust CI/CD pipelines and reliable data processing. Leveraged Python, YAML, and Markdown to implement config-driven dataset loading, model-judge integration, and workflow automation. The work enabled quantitative assessment of model reasoning across diverse benchmarks, supporting scalable, maintainable, and reproducible evaluation in machine learning research.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
11Total
Bugs
2
Commits
11
Features
5
Lines of code
1,298
Activity Months4
Your Network
15 peopleWork History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered the OlymMATH dataset integration for thunlp/SIR-Bench, enabling benchmarking on Olympiad-level math problems with dataset loading, evaluation, and model-judge integration. No major bugs fixed this month. This work expands evaluation capabilities and strengthens the benchmarking platform for math reasoning models. Technologies/skills demonstrated include config-driven dataset loading, evaluation workflow integration, and version-controlled feature delivery (commit 32d6859679539ebbfe8316039f87d095aa8bb4ee).
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered the OlymMATH dataset integration for thunlp/SIR-Bench, enabling benchmarking on Olympiad-level math problems with dataset loading, evaluation, and model-judge integration. No major bugs fixed this month. This work expands evaluation capabilities and strengthens the benchmarking platform for math reasoning models. Technologies/skills demonstrated include config-driven dataset loading, evaluation workflow integration, and version-controlled feature delivery (commit 32d6859679539ebbfe8316039f87d095aa8bb4ee).
April 2025
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for thunlp/SIR-Bench: Expanded benchmarking coverage by adding HLE and AIME2025 dataset support, enabling broader model evaluation on complex reasoning tasks. Implemented dataset loading/config, updated mappings and download URLs, and ensured OSS access for AIME2025. This work enhances evaluation workflows, reproducibility, and opens-source collaboration.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for thunlp/SIR-Bench: Expanded benchmarking coverage by adding HLE and AIME2025 dataset support, enabling broader model evaluation on complex reasoning tasks. Implemented dataset loading/config, updated mappings and download URLs, and ensured OSS access for AIME2025. This work enhances evaluation workflows, reproducibility, and opens-source collaboration.
December 2024
3 Commits • 2 Features
Dec 1, 2024Month: 2024-12. Focused on delivering business value through robustness, scalability, and benchmarking enhancements in thunlp/SIR-Bench. Key outcomes include feature enrichments for longer, compatible QA responses, expanded benchmarking via a new dataset, and reliability improvements in parameter handling and CI thresholds.
3 Commits • 2 Features
Dec 1, 2024Month: 2024-12. Focused on delivering business value through robustness, scalability, and benchmarking enhancements in thunlp/SIR-Bench. Key outcomes include feature enrichments for longer, compatible QA responses, expanded benchmarking via a new dataset, and reliability improvements in parameter handling and CI thresholds.
December 2024
November 2024
5 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for thunlp/SIR-Bench focusing on business value and technical achievements. Delivered notable enhancements to data loading, evaluation, and benchmarking, along with targeted fixes to configuration and data integrity to ensure reliable data processing and reproducible results.
November 2024
5 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for thunlp/SIR-Bench focusing on business value and technical achievements. Delivered notable enhancements to data loading, evaluation, and benchmarking, along with targeted fixes to configuration and data integrity to ensure reliable data processing and reproducible results.
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability87.2%
Architecture88.2%
Performance78.2%
AI Usage25.4%
Skills & Technologies
Programming Languages
MarkdownPythonYAML
Technical Skills
Benchmark DevelopmentCI/CDConfiguration ManagementData EngineeringData EvaluationData LoadingData ManagementDataset HandlingDataset IntegrationDataset ManagementLLM EvaluationLLM IntegrationMachine Learning EvaluationModel ConfigurationNatural Language Processing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline