Papers with general natural language processing
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks (2024.emnlp-main)
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| Challenge: | Large language models (LLMs) have demonstrated considerable proficiency in general natural language processing tasks. |
| Approach: | They propose a parameter-efficient sparsity crafting method which crafts dense models into sparse models using the mixture-of-experts architecture. |
| Outcome: | The proposed method significantly reduces computational costs and GPU memory requirements, while maintaining the quality of approximation in function space. |
Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakers (2023.acl-long)
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| Challenge: | In recent years, machine translation has become very successful for high-resource language pairs. |
| Approach: | They conduct interviews with community leaders, teachers, and language activists to shed light on ethical considerations for the automatic translation of Indigenous languages. |
| Outcome: | The results show that the inclusion of native speakers and community members is vital to performing better and more ethical research on Indigenous languages. |
AraReasoner: Evaluating Reasoning-Based LLMs for Arabic NLP (2025.findings-emnlp)
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| Challenge: | Large language models have shown remarkable progress in reasoning abilities and general natural language processing tasks, yet their performance on Arabic data remains underexplored. |
| Approach: | They compare reasoning-focused LLMs with deepSeek models across 15 Arabic NLP tasks . they use zero-shot, few-shot and fine-tuning to evaluate their capacity for linguistic reasoning . |
| Outcome: | The proposed models outperform strong models on Arabic datasets and are compared with other models. |