Hugging Face 為 Open ASR 排行榜引入「防刷榜機制」，使用私有測試數據打擊 Benchmaxxer
Original: Adding Benchmaxxer Repellant to the Open ASR Leaderboard
Hugging Face has recently made a major update to its popular Open ASR (Automatic Speech Recognition) leaderboard, aimed at combating the…
Hugging Face 宣布為其 Open ASR（自動語音識別）排行榜引入「Benchmaxxer 驅逐劑」。此舉旨在解決模型開發者針對公開基準測試集進行過度優化（即「刷榜」）的問題。通過引入未公開的私有評估數據集，該排行榜將能更真實地反映 ASR 模型在實際應用中的泛化能力，防止虛高的排名誤導社群。
Hugging Face has recently made a major update to its popular Open ASR (Automatic Speech Recognition) leaderboard, aimed at combating the increasingly serious "benchmaxxing" phenomenon in the AI field. "Benchmaxxers" refers to models that achieve extremely high scores on leaderboards by incorporating public benchmark test sets into their training data or by overfitting to specific test sets, while in reality having very poor generalization ability.
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