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Decomposing language models into components

Anthropic

Interpretability research decomposing a transformer layer into thousands of interpretable features that can steer model behavior.

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Research Anthropic

ResearchAuditing language models for hidden objectivesAnthropic ResearchTowards measuring the representation of subjective global opinions in language modelsAnthropic ResearchSycophancy to subterfuge: Investigating reward tampering in language modelsAnthropic ResearchForecasting rare language model behaviorsAnthropic ResearchTracing the thoughts of a large language modelAnthropic ResearchConstitutional Classifiers: Defending against universal jailbreaksAnthropic BlogsLM Link: Use local models on remote devices, powered by TailscaleTailscale LearnNo More Writing SQL for Quick AnalysisMotherduck BlogsConversing with Large Language Models using DaprCncf LearnRemote Components IntroVercel BlogsWeb Components: Working With Shadow DOMSmashingmagazine NewsThe Programming Language Mathematica Marks a MilestoneThenewstack NewsMulticloud Paves the Way for Cloud Native Resiliency ModelsThenewstack BlogsRobust generic functions on slices - The Go Programming LanguageGo BlogsA Proposal for Package Versioning in Go - The Go Programming LanguageGo BlogsContributors Summit 2019 - The Go Programming LanguageGo BlogsGo Protobuf: The new Opaque API - The Go Programming LanguageGo LearnTutorial: Getting started with multi-module workspaces - The Go Programming LanguageGo BlogsWhen To Use Generics - The Go Programming LanguageGo ResourcesGo Wiki: Compiler And Runtime Optimizations - The Go Programming LanguageGo