Papers with data construction strategy
CodeM: Less Data Yields More Versatility via Ability Matrix (2024.findings-acl)
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Daoguang Zan, Ailun Yu, Wei Liu, Bo Shen, Shaoxin Lin, Yongshun Gong, Yafen Yao, Yan Liu, Bei Guan, Weihua Luo, Yongji Wang, Qianxiang Wang, Lizhen Cui
| Challenge: | Recent efforts to train code large language models have been booming recently . however, this will incur significant costs in constructing data and training model considering the countless downstream scenarios. |
| Approach: | They propose a data construction strategy which decouples code LLMs’ abilities into two dimensions and constructs a lightweight training corpus that only covers a subset of target scenarios. |
| Outcome: | The proposed model can train a multilingual multitasking model using less data and training data. |
Sentence Ordering with a Coherence Verifier (2023.findings-acl)
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| Challenge: | Recent sentence ordering studies can be classified into 2 categories: pair-wise ranking-based and sequence generation-based methods. |
| Approach: | They propose a sentence ordering method by plugging a coherence verifier into ranking-based and sequence generation-based methods. |
| Outcome: | The proposed method improves on topological sorting-based and pointer network-based methods with topological and point-based models. |