stanford-crfm/helm
Apr 2025 – Apr 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
Computerized Adaptive Testing (CAT)DocumentationItem Response Theory (IRT)LLM EvaluationPython Development
Sang T. Truong
PROFILE
Sang T. Truong
Developed and integrated the REEval Adaptive Evaluation Framework for the stanford-crfm/helm repository, enabling scalable and reliable evaluation of large language models. Leveraged Computerized Adaptive Testing and Item Response Theory to introduce an adaptive evaluation strategy, allowing for efficient and data-driven assessment of model performance. Implemented a dedicated evaluation runner in Python, expanded documentation in Markdown, and streamlined configuration by integrating REEval parameters into adapter specifications. The work focused on creating a plug-and-play workflow that accelerates adoption and supports reuse across models, demonstrating depth in both technical implementation and documentation to support robust, credible LLM evaluation at scale.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
606
Activity Months1
Your Network
44 peopleWork History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 focus on delivering a scalable, reliable evaluation framework for LLMs within the helm repository. Key feature delivered: REEval Adaptive Evaluation Framework, introducing an adaptive evaluation strategy using Computerized Adaptive Testing (CAT) and Item Response Theory (IRT). Added dedicated evaluation runner, updated documentation, and integrated REEval parameters into adapter specifications to support plug-and-play evaluation workflows.
1 Commits • 1 Features
Apr 1, 2025April 2025 focus on delivering a scalable, reliable evaluation framework for LLMs within the helm repository. Key feature delivered: REEval Adaptive Evaluation Framework, introducing an adaptive evaluation strategy using Computerized Adaptive Testing (CAT) and Item Response Theory (IRT). Added dedicated evaluation runner, updated documentation, and integrated REEval parameters into adapter specifications to support plug-and-play evaluation workflows.
April 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Computerized Adaptive Testing (CAT)DocumentationItem Response Theory (IRT)LLM EvaluationPython Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline