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News/SATFormer: Learning When to Use Early Value Residuals in Transformers
arxiv
PublishedOctober 28, 2026 at 4:00 AM

SATFormer: Learning When to Use Early Value Residuals in Transformers

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arXiv:2605.03953v3 Announce Type: replace Abstract: Recent Transformer architectures expose later layers to representations computed in earlier layers, motivated by the observation that low-level features can become harder to recover as the residual stream is transformed through depth. One such meth

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arxivMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation2harxivCounterfactual Model Testing Under Distribution Shift2harxivCentralized Critics for N-Agent Ad Hoc Teamwork2harxivWhere and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning2h
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