Alignment Research Center
alignment.org
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Overview
The Alignment Research Center studies theoretical approaches to aligning advanced machine learning systems. Its work covers eliciting latent knowledge and formal heuristic arguments. The organisation was founded by a former OpenAI alignment lead.
News
A Mike's-Eye View of ARC's Research
Over the past 15 months or so, ARC's technical agenda has developed quite a bit. The advent of the Matching Sampling Principle (MSP), and ideas like it, has begotten a host of concrete technical problems; progress on those problems has given us more philo
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Announcing the ARC White-Box Estimation Challenge
ARC has teamed up with AIcrowd to launch the ARC White-Box Estimation Challenge, a contest to improve upon our estimation algorithms for random MLPs. The warm-up round begins this week, and later rounds will have a total prize pool of at least $100,000. W
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Mechanistic estimation for expectations of random products
We have developed some relatively general methods for mechanistic estimation competitive with sampling by studying problems that are expressible as expectations of random products. This includes several different estimation problems, such as random halfsp
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Mechanistic estimation for wide random MLPs
This post covers joint work with Wilson Wu, George Robinson, Mike Winer, Victor Lecomte and Paul Christiano. Thanks to Geoffrey Irving and Jess Riedel for comments on the post. In ARC's latest paper, we study the following problem: given a randomly initia
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AlgZoo: uninterpreted models with fewer than 1,500 parameters
This post covers work done by several researchers at, visitors to and collaborators of ARC, including Zihao Chen, George Robinson, David Matolcsi, Jacob Stavrianos, Jiawei Li and Michael Sklar. Thanks to Aryan Bhatt, Gabriel Wu, Jiawei Li, Lee Sharkey, Vi
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