Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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1122 · Feb 201919922001200920172026
7 results for Multi-Language

System supports 102 languages with deep neural networks, reducing error rates and improving recognition speed.

problem Online handwriting recognition for multiple languages with high accuracy and speed.
method Deep neural network architecture, Bézier curves for input encoding, sequence recognition methods.
result Reduced error rates by 20%-40% for most languages, up to 10x faster recognition times.

A deep learning approach generates math word problems in multiple languages.

problem Template-based mechanisms for generating mathematical word problems lack customizability and creativity.
method Character Level Long Short Term Memory Network (LSTM) and POS tags are used to generate and resolve constraints in generated problems.
result The approach generates accurate math word problems in English and Sinhala with over 90% accuracy.

OT domain adaptation improves aphasia detection across languages.

problem Detecting aphasia in low-resource languages with limited data.
method Utilized OT domain adaptation to map linguistic features across multiple languages.
result OT domain adaptation significantly improved F1 scores for French and Mandarin aphasia detection.

Convolutional neural network summarizes code comments across multiple languages.

problem Insufficient or missing comments in source code.
method Language-agnostic encoder-decoder model with open vocabulary.
result Comparable results to state-of-the-art on single-language data; first results on multi-language data.

Deep transfer learning from Persian handwriting improves offline signature verification.

problem Challenges in offline signature verification, especially with skilled forgeries and limited training data.
method Transfer learning approach from Persian handwriting to multi-language OSV, using Residual CNNs for feature learning and SVMs for verification.
result Significant improvement in Equal Error Rate (EER) on UT-Sig dataset (9.80% EER), surpassing state-of-the-art methods.