Neural swipe decoder trained with geometric augmentations on 1M+ swipes generalizes to unseen keyboard layouts by predicting per-point character locations and mapping via inference-time layout.
SHARK 2: a large vocabulary shorthand writing system for pen-based computers
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.HC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
WSTypist is a new RL-based simulation model that reproduces human-like word suggestion strategies, individual differences, and adaptation to design changes in mobile text entry.
citing papers explorer
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FUTO Swipe: Layout-Agnostic Neural Swipe Decoding
Neural swipe decoder trained with geometric augmentations on 1M+ swipes generalizes to unseen keyboard layouts by predicting per-point character locations and mapping via inference-time layout.
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Simulating Word Suggestion Usage in Mobile Typing to Guide Intelligent Text Entry Design
WSTypist is a new RL-based simulation model that reproduces human-like word suggestion strategies, individual differences, and adaptation to design changes in mobile text entry.