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cs.CL2025
TrInk: Ink Generation with Transformer Network
Zezhong Jin, Shubhang Desai, Xu Chen +8
In this paper, we propose TrInk, a Transformer-based model for ink generation, which effectively captures global dependencies. To better facilitate the alignment between the input…
cs.CL2022
SLATE: A Sequence Labeling Approach for Task Extraction from Free-form Inked Content
Apurva Gandhi, Ryan Serrao, Biyi Fang +8
We present SLATE, a sequence labeling approach for extracting tasks from free-form content such as digitally handwritten (or "inked") notes on a virtual whiteboard. Our approach al…