A two-stream Transformer variant that separates state storage from next-token prediction improves validation loss and downstream task performance by 2-3 points over standard Transformers.
FlashAttention: Fast and Memory-Efficient Exact Attention with
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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NightVision recovers LLM hidden dimension to 23% average relative error (9% on MoE) and depth/parameter count to 53% on models >3B parameters using common-set prompting, spectral analysis, and TTFT under single-logit black-box access.
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Black-Box Inference of LLM Architectural Properties with Restrictive API Access
NightVision recovers LLM hidden dimension to 23% average relative error (9% on MoE) and depth/parameter count to 53% on models >3B parameters using common-set prompting, spectral analysis, and TTFT under single-logit black-box access.