Manifold Projection and Iterative Autoencoder Refinement for Masked Language Modeling

arXiv:2609.30288 · cs.CL, cs.LG · Submitted 2026-09-09 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-09

Updated: 2026-09-09

Terminology

• Transformer — 19× in this paper · explained in 2 episodes
• Embeddings — 15× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Iterative Refinement — 9× in this paper · explained in 3 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Hypernetwork — 3× in this paper · explained in 2 episodes
• Perplexity — 3× in this paper · explained in 3 episodes
• Gradient Flow — 2× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Model Merging — 1× in this paper · explained in 2 episodes
• Next Sentence Prediction — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• Low-rank bias, weight decay, and model merging in neural networks
• A Variational AutoEncoder for Transformers with Nonparametric Variational Information Bottleneck
• Denoising Diffusion Generative Models Secretly Calculate Attentions
• RoBERTa: A Robustly Optimized BERT Pretraining Approach

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