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谷歌推出开源框架,要给AI大模型的跑分“立规矩”
3 6 Ke· 2025-05-28 23:34
Core Viewpoint - The AI large model benchmarking landscape is currently fragmented, prompting Google to introduce a standardized evaluation framework called LMEval to streamline the assessment process for AI models [4][16]. Group 1: Current State of AI Benchmarking - The AI large model benchmarking is characterized by a "hundred schools of thought" scenario, with various institutions and private entities creating their own evaluation tools [3][4]. - Notable benchmarks include C-Eval from Tsinghua University, CMMLU from Shanghai Jiao Tong University, and xbench from Sequoia Capital [3]. Group 2: Introduction of LMEval - Google plans to launch LMEval, an open-source framework designed to provide standardized evaluation tools for large language models and multimodal models [4][17]. - LMEval aims to simplify the benchmarking process by allowing researchers and developers to set benchmarks once and conduct standardized evaluations across major platforms like Azure, AWS, and HuggingFace [6][17]. Group 3: Features of LMEval - LMEval supports not only text evaluation but also image and code assessments, addressing current trends in AI [6]. - The framework includes Giskard safety scoring to evaluate the model's ability to avoid generating harmful content, with higher percentages indicating better safety performance [6]. Group 4: Challenges in AI Benchmarking - The rapid evolution of AI models leads to a situation where the effectiveness of benchmarks diminishes quickly, as models can "cram" for tests by training on specific question sets [8][13]. - The industry faces a challenge in creating a scientific and long-lasting evaluation system that accurately reflects AI capabilities, as current solutions tend to be decentralized and varied [16]. Group 5: Implications of LMEval - By introducing LMEval, Google aims to provide a unified standard for evaluating various capabilities of AI models, reducing the need for developers to switch APIs or integrate different test sets [17].