Carlos Plou developed FALCON-Bench, a benchmarking framework for evaluating multimodal large language models on one-hour video tasks within the EvolvingLMMs-Lab/lmms-eval repository. He designed YAML-driven configurations and Python utility functions to streamline task processing and evaluation, enabling reproducible and scalable model comparisons. His work focused on building a robust evaluation pipeline that integrates seamlessly with existing codebases, supporting fair cross-model analysis and faster iteration cycles. By leveraging skills in benchmarking, data processing, and machine learning, Carlos addressed the need for standardized multimodal LLM evaluation, delivering a technically sound solution with depth in both configuration management and evaluation methodology.