Summary
This paper addresses the challenge of evaluating Large Language Models (LLMs), noting that traditional benchmarks often fail to capture real-world usefulness. It focuses on "vibe-testing," an informal, experience-based evaluation method users commonly employ, such as comparing models on personal coding tasks. The research aims to understand and formalize this prevalent but unstructured approach to enable systematic analysis and reproducibility.
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[Paper] Ruka-v2: Tendon Driven Open-Source Dexterous Hand with Wrist and Abduction for Robot Learning
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