Metacognitive Consolidation lets LLMs accumulate reusable meta-reasoning skills from past episodes to improve future performance across benchmarks.
The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=
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KVM is a new block-recurrent compressed KV attention that turns transformers into O(N) chunked RNNs or growable sublinear-memory models while remaining implementable with standard operations.
MDN parallelizes stepwise momentum for delta linear attention using geometric reordering and dynamical systems analysis, yielding performance gains over Mamba2 and GDN on 400M and 1.3B models.
citing papers explorer
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Beyond Meta-Reasoning: Metacognitive Consolidation for Self-Improving LLM Reasoning
Metacognitive Consolidation lets LLMs accumulate reusable meta-reasoning skills from past episodes to improve future performance across benchmarks.
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Key-Value Means: Transformers with Expandable Block-Recurrent Compressed Memory
KVM is a new block-recurrent compressed KV attention that turns transformers into O(N) chunked RNNs or growable sublinear-memory models while remaining implementable with standard operations.
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MDN: Parallelizing Stepwise Momentum for Delta Linear Attention
MDN parallelizes stepwise momentum for delta linear attention using geometric reordering and dynamical systems analysis, yielding performance gains over Mamba2 and GDN on 400M and 1.3B models.