Papers by Velayuthan Menan
Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora (2024.eacl-long)
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| Challenge: | Existing web-mined corpora for low-resource languages have serious quality issues, especially for lowresource language pairs. |
| Approach: | They ranked each corpus according to a similarity measure and evaluated different portions of this ranked corpus. |
| Outcome: | The results show that the quality of web-mined corpora for low-resource languages is significantly different from human-curated corporats. |
Egalitarian Language Representation in Language Models: It All Begins with Tokenizers (2025.coling-main)
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| Challenge: | Tokenizers influence how language is represented in large language models . pre-tokenization choices can be problematic for some languages . |
| Approach: | They propose a tokenization algorithm that incorporates graphemes to improve tokenization . they validate this algorithm with Tamil, Sinhala, and Hindi scripts . |
| Outcome: | The proposed method outperforms tokenizers on Tamil, Sinhala, and Hindi scripts. |
Improving the Quality of Web-mined Parallel Corpora of Low-Resource Languages using Debiasing Heuristics (2025.emnlp-main)
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| Challenge: | Parallel Data Curation (PDC) techniques aim to filter out noisy parallel sentences from web-mined corpora. |
| Approach: | They propose to rank parallel sentences using similarity scores on sentence embeddings derived from Pre-trained Multilingual Language Models (multiPLMs) . previous research has shown that the choice of multiPLM significantly impacts the quality of the filtered parallel corpus. |
| Outcome: | The proposed methods reduce disparities between multiPLMs while producing better results. |