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Pose a question about one of the following articles:
“[Online images amplify gender bias](https://www.nature.com/articles/s41586-024-07068-x),” 2024. Guilbeault, Douglas, Solène Delecourt, Tasker …
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## Ref
- CS41 [[课程主页]](https://stanfordpython.com/#lecture)
- [ ] Test-Driven Development with Python [[youtube]](https://www.obeythetestinggoat.com/book/praise.harry.html)
- 这是一本非常棒的…
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A large structured hex (eventually mixed) mesh is needed and there are issues getting a mesh generator to easily produce this.
The [`matchedReader` branch](https://github.com/cwsmith/core/tree/matc…
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[paper](https://arxiv.org/pdf/2204.14198.pdf)
## TL;DR
- **I read this because.. :** #116 읽고 나서 읽고 싶어짐. 예전에 성현님이 소개해주셨는데 디테일 모름. GPT 열풍으로 요즘 다시 많이 언급됨.
- **task :** Vision Language Model in g…
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Hello,
I really like the idea to combine spacy with google stuff, thanks! I got some seemingly random deadlock problem...
I am basically doing n*(n-1)/2 comparison on 50K papers by their titles …
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**Dataset download link :** https://nlp.stanford.edu/projects/snli/snli_1.0.zip
**Dataset website :** https://nlp.stanford.edu/projects/snli/
**Paper :** https://nlp.stanford.edu/pubs/snli_paper…
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The plan here is to use fairly basic repeated string substitutions to form a "novel", using public domain texts as inputs, and command line bash tools to organise the source material in various ways.
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hornc updated
4 years ago
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Post a reading of your own that uses deep learning for social science analysis and understanding, with a focus on text data.
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因为 task-specific data 有限，难蒸馏出好 student model，所以用 mixup 增强数据，teacher 对插值的输入预测，student 学习该预测结果(loss_3，带调节系数超参)，直接学插值输入对应的插值标签(loss_2，带调节系数超参)，学习原始数据(loss_1，无系数)。提供了一些理论证明，在GLUE上做了实验有效。
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