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Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability

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arxiv 2412.18551 v1 pith:TLAJUZ6O submitted 2024-12-24 cs.CL

Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability

classification cs.CL
keywords libra-leaderboardsafetybalancedcapabilityleaderboardllmsmodelsperformance
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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To address this gap, we introduce Libra-Leaderboard, a comprehensive framework designed to rank LLMs through a balanced evaluation of performance and safety. Combining a dynamic leaderboard with an interactive LLM arena, Libra-Leaderboard encourages the joint optimization of capability and safety. Unlike traditional approaches that average performance and safety metrics, Libra-Leaderboard uses a distance-to-optimal-score method to calculate the overall rankings. This approach incentivizes models to achieve a balance rather than excelling in one dimension at the expense of some other ones. In the first release, Libra-Leaderboard evaluates 26 mainstream LLMs from 14 leading organizations, identifying critical safety challenges even in state-of-the-art models.

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