Tag
Rutgers researchers audit 41 model entries from 17 language model families using 24 pretraining indicators from the 2025 Foundation Model Transparency Index, finding that later releases do not consistently preserve earlier pretraining disclosures, with stable scores often masking offsetting gains and losses.
whatmodel.sh 的作者分析了 1,629 个已发布的基准测试结果，发现 AI 实验室自报的分数平均比独立测试机构高出 6.4%，相关数据集与代码均已开源。
Dario Amodei suggests that closed-weight, secret models may be worse than open-weight ones, sparking discussion on AI transparency and safety.
This article provides a systematic and comprehensive overview of AI explainability, covering its needs (debugging, compliance, safety), classic methods, and cutting-edge challenges, emphasizing that faithful explanations are more important than plausible ones.
ModSleuth is a new tool that traces the dependencies of modern LLMs, revealing that models like OLMo 3 and Nemotron 3 rely on hundreds of other models and datasets, highlighting the shift from human-only to AI-generated training data.