AI Evaluation

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Friday, 28 August 2026

An Anthropic researcher just gave us a peek at self-improving AI

TechCrunch 1 month ago 41 ● 5 sources

Anthropic published a paper describing an automated system that improves AI performance on alignment benchmarks by running iterative literature search, method proposals, and short training loops. The system trained for 30 minutes per method iteration and improved results on all 10 specified misaligned-behavior benchmarks without lowering overall performance. This suggests automated post-training for alignment could become practical soon, shifting some alignment research work toward automation rather than humans.

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AI Safety Anthropic AI Evaluation AI Alignment

LLMs Are Not (Consistently) Bayesian: Quantifying Internal (In)consistencies of LLMs’ Probabilistic Beliefs

Apple Machine Learning Research 1 month ago 16 ● 2 sources

The article proposes treating large language models as information processing rules and measuring how far their belief updates deviate from Bayes updates. It introduces the “information processing gap” as the quantitative way to track these internal probabilistic (in)consistencies. As a result, the work frames LLM uncertainty behavior in terms of measurable Bayes-update errors rather than assuming consistent Bayesian reasoning.

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Large Language Models AI Evaluation Model Evaluation Scientific Research

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