Papers by Yaniv Romano

1 papers
Segment-Based Attention Masking for GPTs (2025.acl-long)

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Challenge: Causal masking is a fundamental component in Generative Pre-Trained Transformers (GPT) models, playing a crucial role during training.
Approach: They propose to apply causal masking to all input tokens step-by-step, mimicking the generation process.
Outcome: The proposed model can process the entire user prompt at once, but it is applied to all input tokens step-by-step, mimicking the generation process.

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