October 2025 (2025-10) — Monthly summary for Open-Finance-Lab/FinLLM-Leaderboard focused on delivering dataset documentation and improving repository hygiene to support benchmarking and onboarding.

June 2025 focused on stabilizing location data access for ScottyLabs/cmueats. Delivered reliability improvements for the Location Data Retrieval API, including server-side redirects and generalized JSON routing. Fixed critical issues that reduced error rates and improved downstream data access. These changes enhance data quality for location-based features and reduce support overhead.

April 2025 monthly summary for Open-Finance-Lab/FinLLM-Leaderboard focusing on delivered features and bug fixes, business value, and technical accomplishments.

March 2025 monthly summary for Open-Finance-Lab focused on delivering benchmarking capabilities, data curation, and documentation enhancements across two repositories: FinLLM-Leaderboard and FinRL_Contest_2025. Key outcomes include the introduction of structured evaluation reporting for DeepSeek distilled models, expansion of fine-tuning datasets for GAAP tagging, and expanded FiNER/FNXL dataset documentation and testing guidance. No major bug fixes were recorded this month; the emphasis was on data quality, reproducibility, and measurable business value. Impact highlights: - Enabled side-by-side benchmarking of DeepSeek distilled models with per-model and per-task results, including accuracy, F1-score, and MCC. - Expanded GAAP-tagging data support with new fine-tuning datasets and refined US GAAP tag coverage for FinLLM tasks. - Improved evaluation and testing coverage through FiNER/FNXL documentation and additional testing subsets (FiNER-139, FNXL). - Strengthened dataset organization and reproducibility for benchmarking workflows, accelerating iteration and model improvements. Technologies/skills demonstrated: - Python-based reporting and data organization for model evaluation. - Dataset curation and fine-tuning data preparation for NLU/Governance tasks. - Comprehensive documentation and testing guidance to support robust evaluation and onboarding of new datasets. - Benchmarking and research-first workflows enabling faster, data-driven decision-making for model development.

February 2025 monthly summary for Open-Finance-Lab/FinLLM-Leaderboard: Delivered an end-to-end zero-shot benchmarking tutorial for financial QA, plus a targeted documentation improvement. The work focuses on reducing onboarding time, enabling reproducible model evaluation, and showcasing practical business-value through a ready-to-use benchmarking workflow.