Papers with direct generation method
Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and Sundanese (2024.emnlp-main)
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| Challenge: | Large Language Models (LLMs) are increasingly being used to generate synthetic data for training and evaluating models. |
| Approach: | They investigate the effectiveness of using Large Language Models to generate culturally relevant commonsense QA datasets for Indonesian and Sundanese languages using both LLMs and human annotators. |
| Outcome: | The proposed model generates 4.5K questions per language, compared with 4.5k for Indonesian and 4.5km for Sundanese. |
Threading the Needle: Reweaving Chain-of-Thought Reasoning to Explain Human Label Variation (2025.emnlp-main)
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| Challenge: | Recent advances in large language models have shown the power of chain-of-thought reasoning in improving complex decision-making tasks. |
| Approach: | They propose a pipeline that generates chain-of-thought (CoT) explanations from CoTs with improved accuracy. |
| Outcome: | The proposed pipeline outperforms a direct generation method and baselines on three datasets. |