| アイテムタイプ |
デフォルトアイテムタイプ（フル）(1) |
| 公開日 |
2023-12-12 |
| タイトル |
|
|
タイトル |
TUA1 at NTCIR-17 FinArg-1 Task |
|
言語 |
en |
| 作成者 |
Daichi Yamane
Fei Ding
Xin Kang
|
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Transformer |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Fine-Tuning |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Argument Mining |
| 主題 |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Financial Engineering |
| 内容記述 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
This paper reports on the results produced by the TUA1 team in the Earnings Conference Call (ECC), Task 1 of Finarg-1 of NTCIR-17. The ECC is divided into two subtasks. One is Argument Unit Identification (AUI) and the other is Argument Relation Identification (ARI). There are two proposed methods. The first is to tune a pre-trained model based on the transformer architecture using prompts. This method was applied to both Argument Unit Identification and Argument Relation Identification. The second approach employs Cost-Sensitive Learning on pre-trained models, which were previously tuned. This was exclusively used for Argument Relation Identification.In the provided training and validation data for Argument Relation Identification, the correct labels were markedly unbalanced, with some specific labels being notably scarce. Cost-Sensitive Learning proves effective for such unbalanced datasets, often yielding higher results than pure pre-trained models alone. In our experiments involving prompt tuning, we leveraged the Weighted Random Sampler technique to further enhance accuracy on the unbalanced data.Experiments using the aforementioned methods revealed that we achieved the best results for Argument Relation Identification, and secured third place for Argument Unit Identification. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
NII Institutional Repository |
|
言語 |
en |
| 日付 |
|
|
日付 |
2023-12-12 |
|
日付タイプ |
Issued |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
|
資源タイプ |
conference paper |
| ID登録 |
|
|
ID登録 |
10.20736/0002001288 |
|
ID登録タイプ |
JaLC |
| 関連情報 |
|
|
関連タイプ |
isReferencedBy |
|
|
識別子タイプ |
URI |
|
|
関連識別子 |
https://research.nii.ac.jp/ntcir/ntcir-17/index.html |
|
|
言語 |
en |
|
|
関連名称 |
NTCIR-17 Conference |
| 開始ページ |
|
|
開始ページ |
none |
| 会議記述 |
|
|
|
会議名 |
NTCIR-17 Conference |
|
|
言語 |
en |
|
回次 |
17 |
|
|
主催機関 |
National Institute of Informatics |
|
|
言語 |
en |
|
|
開始年 |
2023 |
|
|
開始月 |
12 |
|
|
開始日 |
12 |
|
|
終了年 |
2023 |
|
|
終了月 |
12 |
|
|
終了日 |
15 |
|
|
開催期間 |
December 12-15, 2023 |
|
|
言語 |
en |
|
|
開催会場 |
National Institute of Informatics |
|
|
言語 |
en |
|
開催国 |
JPN |
06-NTCIR17-FINARG-YamaneD.pdf (393 KB)
