Papers by Jie-Jyun Liu
Parameter Selection: Why We Should Pay More Attention to It (2021.acl-short)
Copied to clipboard
| Challenge: | supervised learning is a challenging process due to the huge number of parameter combinations. |
| Approach: | They present an example of parameter selection in supervised learning . authors use a set of frequently occurring labels without a parameter tuning . they say this illustrates the seriousness of parameter tuning in a supervised field . |
| Outcome: | The proposed study shows that without adequate attention, the research progress can be uncertain or even illusive. |
Linear Classifier: An Often-Forgotten Baseline for Text Classification (2023.acl-short)
Copied to clipboard
| Challenge: | Large-scale pre-trained language models such as BERT are popular solutions for text classification. |
| Approach: | They argue that large-scale pre-trained language models such as BERT are popular solutions for text classification . authors argue that running a simple baseline like linear classifiers on bag-of-words features is important for text classification . |
| Outcome: | The proposed approach may only sometimes get satisfactory results for some problems. |