A Tabu-based algorithm learns time-ordered causal graphs from time series by optimizing per-edge lags with a decomposable BIC score and explicit lag penalty.
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Sparse replacement layers decompose the MLP and attention modules of a chess-playing transformer to reveal verifiable tactical reasoning pathways and parallel computation patterns.
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Time series causal discovery with variable lags
A Tabu-based algorithm learns time-ordered causal graphs from time series by optimizing per-edge lags with a decomposable BIC score and explicit lag penalty.
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Tracing the Thought of a Grandmaster-level Chess-Playing Transformer
Sparse replacement layers decompose the MLP and attention modules of a chess-playing transformer to reveal verifiable tactical reasoning pathways and parallel computation patterns.