Papers with adaptations
Data and Model Centric Approaches for Expansion of Large Language Models to New languages (2025.emnlp-tutorials)
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| Challenge: | Existing LLMs mainly support English alongside a handful of high resource languages . this leaves a major gap for most low-resource languages despite increasing pace of research . |
| Approach: | This tutorial examines approaches to expand the language coverage of LLMs . they look at tokenizer training, pre-training, instruction tuning, alignment, evaluation, etc. |
| Outcome: | This tutorial examines approaches to expand the language coverage of LLMs . it provides an efficient and viable path to bring LLM technologies to low-resource languages . |
Addressing Noise in Multidialectal Word Embeddings (P18-2)
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| Challenge: | Dialectal Arabic (DA) is problematically noisy and lacks a large corpus of non-noisy words. |
| Approach: | They propose to use word embedding tools to maximize the informative content leveraged in each training sentence and analyze methods for representing disparate dialects in one embeddable space. |
| Outcome: | The proposed methods improve performance on low and high frequency words while preserving accuracy on low frequency forms. |