The Quandary Den artificial life model shows that neutral evolution can generate interlocking complexity in protein-like systems via subfunctionalization and masking mechanisms without needing more information or fitness benefits.
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The paper formulates LLM-as-judge evaluation as a two-stage missing-data problem and derives sample-size formulas via doubly robust estimators to achieve desired power while allocating more human reviews where LLM predictability is low.
mlr3torch introduces an extensible deep learning framework in R that integrates torch models into the mlr3 ecosystem via graph-based architectures for classification, regression, and multimodal tasks.
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Neutrally Evolving Interlocking Complexity in the Quandary Den
The Quandary Den artificial life model shows that neutral evolution can generate interlocking complexity in protein-like systems via subfunctionalization and masking mechanisms without needing more information or fitness benefits.
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Augmenting Human Evaluation with LLM Judges: How Many Human Reviews Do You Need?
The paper formulates LLM-as-judge evaluation as a two-stage missing-data problem and derives sample-size formulas via doubly robust estimators to achieve desired power while allocating more human reviews where LLM predictability is low.
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mlr3torch: A Deep Learning Framework in R based on mlr3 and torch
mlr3torch introduces an extensible deep learning framework in R that integrates torch models into the mlr3 ecosystem via graph-based architectures for classification, regression, and multimodal tasks.