dailyai.report

Over 720 fine-tuned LLMs comprise Pando, a new benchmark designed to test how well interpretability methods uncover known decision rules. Researchers found gradient-based methods outperform blackbox baselines, while non-gradient approaches struggle. This dataset provides a controlled environment to measure rationale faithfulness. Practitioners can now more accurately validate which interpretability tools actually reveal a model's internal logic.