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This guide outlines a concrete workflow for evaluating large language models against "SPI-incompatible" behaviors, moving from high-level strategy to actionable next steps and specific criteria for identifying harmful reasoning patterns. By defining unambiguous benchmarks for these incompatibilities, the research aims to establish a rigorous framework for detecting and mitigating safety risks in model development. The open invitation for collaboration suggests a community-driven approach to refining these evaluation protocols before broader implementation.
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[Linkpost] Evals for “SPI-incompatible” behavior & reasoning: Guide to initial research

LessWrong1 min de cititArticolul și perspectiva sunt în engleză.

In Part I of CLR's safe Pareto improvements (SPI) agenda, we gave our high-level strategy for evaluating models for SPI-incompatible behavior and reasoning. This guide gives more details on how I’m thinking about executing on this strategy, especially: the kind of workflow I think we should use, to start out; next steps building on what I’ve tried so far; and my rough sense of what counts as unambiguously bad “SPI-incompatibilities”. If you’re interested in collaborating on the next steps, please get in touch! I’d be happy to flesh things out more, and invite you to the private git repo. Discuss

In Part I of CLR's safe Pareto improvements (SPI) agenda, we gave our high-level strategy for evaluating models for SPI-incompatible behavior and reasoning. This guide gives more details on how I’m thinking about executing on this strategy, especially:

my rough sense of what counts as unambiguously bad “SPI-incompatibilities”.

If you’re interested in collaborating on the next steps, please get in touch! I’d be happy to flesh things out more, and invite you to the private git repo.

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