One Token Is Enough: Improving Diffusion Language Models with a Sink Token

Researchers have identified an instability in Diffusion Language Models (DLMs) known as the moving sink phenomenon, which affects model performance. They propose adding a single extra "sink token" to stabilize attention sinks, improving DLM robustness and performance without requiring semantic content, offering a simple solution for enhancing text generation models.

Read the full article at arXiv cs.CL (NLP)

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