Paper: Orchestrator and Task-Framing Effects Dominate Fine-Tuning in Real-World Agent Evaluation of a Quantized 31B ModelAuthors: Kiko Cisneros, Claude Sonnet 4.6 · Utopia IA, May 2026Code: github.com/KikoCisBot/gemma4-31b-study
📄 See paper4_orchestrator_dominance.pdf in the Files tab.
Standard benchmarks (BFCL, HumanEval) do not predict real-world agent capability. A model scoring 95% BFCL scores 0/10 on a real autonomous task… See the full description on the dataset page:
https://huggingface.co/datasets/KikoCis/real-world-agent-benchmark.
