New metrics KSS and KPS are introduced to evaluate multilingual machine unlearning quality and cross-language consistency in LLMs, addressing limitations of single-language evaluation protocols.
W iki M atrix: Mining 135 M Parallel Sentences in 1620 Language Pairs from W ikipedia
6 Pith papers cite this work, alongside 146 external citations. Polarity classification is still indexing.
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Manual audit shows web-scraped Lombard corpora are largely noisy and biased toward Western varieties over Eastern ones.
The study filters non-English Wikipedia, reveals quality problems, proposes a 4-level ranking, and shows filtered data matches or beats raw data in language modeling with largest gains for lower-quality editions.
A multi-stage pipeline that pivots Traditional Mongolian script through Cyrillic before translation improves MT quality across multiple backbones and target languages, and generates useful synthetic parallel data.
Large-scale benchmarks of multilingual embeddings and QE models show no universal performer; direction-aware routing and calibration recommended for parallel data assessment.
Lius improves LLM translation for Kupang Malay by 4-13 points over baselines via continual instruction tuning with dictionary-derived instructions.
citing papers explorer
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Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation
New metrics KSS and KPS are introduced to evaluate multilingual machine unlearning quality and cross-language consistency in LLMs, addressing limitations of single-language evaluation protocols.
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"Chi nas dal soch el sent de legn" -- Auditing Text Corpora for Lombard
Manual audit shows web-scraped Lombard corpora are largely noisy and biased toward Western varieties over Eastern ones.
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How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP
The study filters non-English Wikipedia, reveals quality problems, proposes a 4-level ranking, and shows filtered data matches or beats raw data in language modeling with largest gains for lower-quality editions.
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CoPiT: Cognitive Pivot Translation for Digraphic Low-Resource Mongolian in the Traditional Script
A multi-stage pipeline that pivots Traditional Mongolian script through Cyrillic before translation improves MT quality across multiple backbones and target languages, and generates useful synthetic parallel data.
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Model-Based Quality Assessment for Massively Multilingual Parallel Data
Large-scale benchmarks of multilingual embeddings and QE models show no universal performer; direction-aware routing and calibration recommended for parallel data assessment.
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Lius: Translation Model Based Instructional Lingustic Using Continual Instruction Tuning In Kupang Malay
Lius improves LLM translation for Kupang Malay by 4-13 points over baselines via continual instruction tuning with dictionary-derived instructions.