Papers by Tongxi Wang

1 papers
FBS: Modeling Native Parallel Reading inside a Transformer (2026.findings-acl)

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Challenge: Existing acceleration methods largely patch the autoregressive pipeline and miss core human-reading ingredients.
Approach: They propose a trainable loop that injects a causal loop into Transformers via a 'parafoveal' approach.
Outcome: The proposed model improves quality-efficiency trade-off without increasing parameters . ablations show the three modules are complementary .

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