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cs.CL2026
No Single Tokenizer Feature Reliably Predicts Downstream Language Model Performance
Antonio Lopardo, Luis Frentzen Salim, Shikhar Srivastava +3
Tokenization is a critical component of the language modeling pipeline, but it is poorly understood. Tokenizers can impact downstream performance, but there is currently mixed evid…
cs.CL2026
Weight Tying Biases Token Embeddings Towards the Output Space
Antonio Lopardo, Avyukth Harish, Catherine Arnett +1
Weight tying, i.e. sharing parameters between input and output embedding matrices, is common practice in language model design, yet its impact on the learned embedding space remain…