Comments (5)
您好,非常感谢您对我们工作的关注。关于MEGA在MNER数据上的实验结果是来自于MEGA的源码进行复现,其中MNER的数据集处理流程与MRE是一样的。我们之前的MNER数据集处理之后的结果可能因为服务器的迁移和删容而丢失了,您仍然可以参考MEGA上链接的imgSG的处理代码进行处理。
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请问您还有其它问题吗?如有论文细节或复现任何问题欢迎提issue😊
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请问您还有其它问题吗?如有论文细节或复现任何问题欢迎提issue😊
感谢你们的工作,一个额外的问题是 请问你们提供的Twitter15数据集是你们修改之后的还是原数据集呢?我看您提供的链接里Twitter15训练集有4000个数据,Twitter17训练集有3373个数据和原数据集一样。但是您附录里数据数量好像不太一样?麻烦您了,第一次接触有些地方理解的不大对。
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您好,我们提供的数据集是修复以后的数据,您提到的附录里数据数量不一样可以具体描述一下吗?
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您好,我们提供的数据集是修复以后的数据,您提到的附录里数据数量不一样可以具体描述一下吗?
抱歉,感谢您的耐心,应该是我搞错了
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Related Issues (18)
- How to test the RE models HOT 2
- 关系数据集中object image的获取方案? HOT 2
- RuntimeError: mat1 dim 1 must match mat2 dim 0 HOT 2
- What are the details of using the visual grouding tool? HOT 2
- No error HOT 2
- Question about Twitter-2015 HOT 2
- data preprocess HOT 1
- 关于MRE任务中F1计算的问题 HOT 2
- 关于 使用 visual grouding 工具提取局部视觉图像的代码实现,能提供一下吗 HOT 4
- question HOT 5
- Request for the object image data HOT 2
- Question about the "Segmentation fault (core dumped)" error
- Not putting parameters into optimizer but still trainable HOT 3
- Twitter15数据集修改部分实体类别 HOT 4
- RE数据集下载太慢 HOT 7
- Twitter15_ckpt, Twitter17_ckpt,re_ckpt需要访问权限 HOT 2
- Question about get_visual_prompt HOT 2
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