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Braco is a lightweight four-step coder that combines transform-basis truncation, input-independent basis-coordinate embeddings, budget-dependent orthogonal re-parameterization, and learned spatial residual tokens from lightweight pooling that forms the favorable empirical accuracy-efficiency frontier under compression.
This work introduces RODE, which gives the radial and directional components separate update rules and step sizes in the matrix Frobenius norm, and suggests that decoupling radial and directional dynamics offers a more effective and controllable approach to matrix optimization.
This work presents the first systematic characterization of SDC vulnerability across major computation interfaces in both the forward and backward passes of Transformer training, and proposes TrainSDC, a characterization-guided protection framework consisting of Q/K-path recomputation, residual-gain monitoring, and exp...
The results suggest that robust Agentic EDA requires not only stronger models but also structured tool interfaces, persistent design context, controlled execution, and process-level evaluation.
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