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Beyond Static and Linear: What Attention Constraints Best Fit Human Reading Times?

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.23818v1 Announce Type: new Abstract: Transformer-based language models are widely used as models of human language processing, yet their attention mechanisms allow lossless access to the full preceding context, unlike the limited memory systems of humans. We hypothesize that installing m…

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  1. 2026-08-26 04:00 · arXiv cs.CL
    Beyond Static and Linear: What Attention Constraints Best Fit Human Reading Times?

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