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Reinforcement learning: An introduction , author=

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fields

cs.CL 1 stat.ME 1

years

2026 1 2022 1

verdicts

UNVERDICTED 2

representative citing papers

An adaptive variance estimator for relative sparsity

stat.ME · 2026-05-04 · unverdicted · novelty 6.0

A new adaptive variance estimator for relative sparsity coefficients is introduced that fully utilizes the prior asymptotic normality theorem and incorporates variable selection effects.

ST-MoE: Designing Stable and Transferable Sparse Expert Models

cs.CL · 2022-02-17 · unverdicted · novelty 6.0

ST-MoE introduces stability techniques for sparse expert models, allowing a 269B-parameter model to achieve state-of-the-art transfer learning results across reasoning, summarization, and QA tasks at the compute cost of a 32B dense model.

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Showing 2 of 2 citing papers.

  • An adaptive variance estimator for relative sparsity stat.ME · 2026-05-04 · unverdicted · none · ref 222

    A new adaptive variance estimator for relative sparsity coefficients is introduced that fully utilizes the prior asymptotic normality theorem and incorporates variable selection effects.

  • ST-MoE: Designing Stable and Transferable Sparse Expert Models cs.CL · 2022-02-17 · unverdicted · none · ref 28

    ST-MoE introduces stability techniques for sparse expert models, allowing a 269B-parameter model to achieve state-of-the-art transfer learning results across reasoning, summarization, and QA tasks at the compute cost of a 32B dense model.