A multilingual AI interface maps text to contextually relevant pictograms with expert-rated semantic appropriateness above 90 percent across English, French, Italian, Spanish, and Arabic for reading rehabilitation.
Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols,
1 Pith paper cite this work. Polarity classification is still indexing.
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Pith paper citing it
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cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
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Robust Multilingual Text-to-Pictogram Mapping for Scalable Reading Rehabilitation
A multilingual AI interface maps text to contextually relevant pictograms with expert-rated semantic appropriateness above 90 percent across English, French, Italian, Spanish, and Arabic for reading rehabilitation.