Probability Distributions Computed by Hard-Attention Transformers

arXiv — cs.CL•Monday, November 3, 2025 at 5:00:00 AM

A recent study on arXiv has shed light on the expressivity of transformer language models, emphasizing their role in generating strings probabilistically rather than just recognizing them. This research reveals that by making transformer language recognizers autoregressive, their expressivity can be enhanced. This finding is significant as it opens new avenues for improving language models, which are crucial in various applications like natural language processing and AI-driven communication.

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