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Recently, I have been studying this paper and I am not very clear about formula 4 in the paper. The spatial weight map M is generated for each type of manipulation operation. Therefore, if there are s…
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It seems they are somehow similar and could you please describe the difference between them? Thank you!
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## Motivation #
There is significant interest in vLLM supporting encoder/decoder models. Issues #187 and #180 , for example, request encoder/decoder model support. As a result encoder/decoder supp…
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Thanks for your great work! I want to know how the Cross-Attention Decoder is implemented. Do we need to determine the positional relationship between mask tokens and unmask tokens?
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作者您好,我在module_util.py中看到了CrossLinearAttention,看起来应该是用来替换UNet尺寸较大的几个阶段的Attention的,但是为什么最终没有使用呢?
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@kovalexal In the paper, the de-coupled cross-attention allows text and image to go through different Linear layers respectively, and then perform cross-attention and add the results. However, in the…
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**Is your feature request related to a problem? Please describe.**
I'm able to use the `onnxruntime.transformers` codebase to optimize Tranformer-based model using self-attention, however it's not …
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Hi, your work is amazing!
After reading your paper, I have one question. What exactly is the difference between Cross Frame Attention and the Sparse-Causal Attention from the Tune-A-Video paper?
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if crossattn:
detach = torch.ones_like(key)
detach[:, :1, :] = detach[:, :1, :]0.
key = detachkey + (1-detach)key.detach()
value = detachvalue + (1-detach)*value.detach()
Why stop the gradient …
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Dear professor Peng Qian,
Recently I have read the latest paper published by your team in IJCAI-21-《Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and…