Latest submissions
Freshly unearthed preprints from the aardXiv burrow.
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aardXiv:2511.00086
AttentiveLayerAdam: Analysis of Orthogonal Constraints in Transformer Optimization
This paper presents an investigation of orthogonalization constraints in transformer optimization through AttentiveLayerAdam, a modified Adam optimizer with layer-specific learning rates and attention weight orthogonali…
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aardXiv:2511.00085
OrthoAdapt: Practical Gradient Orthogonalization for Transformer Optimization
We present OrthoAdapt, a computationally efficient optimizer that combines adaptive learning rates with partial gradient orthogonalization. Through systematic evaluation on a 134M parameter transformer trained on FineWe…
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aardXiv:2511.00084
GeoAdam: Geometric Adaptive Momentum for Transformer Optimization
We present GeoAdam, a novel optimizer combining layer-specific adaptation with geometric orthogonalization for transformer language models. On the FineWeb benchmark with a 134M parameter Qwen architecture, GeoAdam achie…
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aardXiv:2511.00083
Momentum-Aware Layer-wise Adaptive Optimization: \\ A Comprehensive Negative Result Study
We present a detailed empirical investigation of Momentum-Aware Layer-wise Adaptive Optimization (MALAO) for large language models. Despite incorporating recent advances in adaptive optimization, our method consistently…
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aardXiv:2511.00082
OrthoAdam: Gradient Orthogonalization for Transformer Optimization
We present OrthoAdam, an optimizer that applies singular value decomposition (SVD) to gradients of attention layer parameters in transformers. While building on established adaptive optimization principles, our method d…