However, representing visual data is challenging for SSMs due to the position-sensitivity of visual data and the requirement of global context for visual understanding. In this paper, we show that the reliance of visual representation learning on self-attention is not necessary and propose a new ...
in usual RNN you can adjust the time-decay of a channel from say 0.8 to 0.5 (these are called "gates"), while in RWKV you simply move the information from a W-0.8-channel to a W-0.5-channel to achieve the same effect. Moreover, you can fine-tune RWKV ...
By their reckoning, we’ve somehow always got enough air traffic controllers, and they’re somehow never working hard enough in a life-and-death critical craft in which their misstatement of the same absolutely psychotic-sounding sequence of numbers and NATO Phonetic letters they’ve said into a...
一位非 Transformer 研究者表示,Mamba 完全只用 recurrent(循环)结构,不用 attention,所以它在做下一个 token 的预测时,其内存大小永远固定,并不会随时间增加而增加;但它的问题在于滚动的过程中 memory 非常小,即其外推能力也比较弱。 上述研究者认为,微软亚研提出的 RetNet,走的也是完全 recurrent 思路。RetNet...
Learn how Darktrace detected the Gozi ISFB malware, a type of banking trojan, with Self-Learning AI. Stay informed about the latest cybersecurity threats.
Lombard Theological School in Chicago is including Islam in its initiative to train clergy in the context of faiths other than their own, and Claremont School of Theology in California will add clerical training for Muslims and Jews to its curriculum this fall. Georgetown University recently ...
"A Federated Learning-Friendly Approach for Parameter-Efficient Fine-Tuning of SAM in 3D Segmentation." ArXiv (2024). [paper] [code] [2024.07] RoBox-SAM:Yuhao Huang, Xin Yang, Han Zhou, Yan Cao, Haoran Dou, Fajin Dong, Dong Ni. ...
To address this problem, we introduce a 3D smoothing filter which constrains the size of the 3D Gaussian primitives based on the maximal sampling frequency induced by the input views, eliminating high-frequency artifacts when zooming in. Moreover, replacing 2D dilation with a 2D Mip filter, ...
So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding (using the final hidden state). Our latest version is RWKV-6, which is easily Mamba level, and simpler ;) https://twitter....
"Synergizing In-context Learning Model and SAM in Medical Image Segmentation." ArXiv (2024). [paper] [2024.02] UnCLe SAM: Amin Ranem, Mohamed Afham Mohamed Aflal, Moritz Fuchs, Anirban Mukhopadhyay. "UnCLe SAM: Unleashing SAM’s Potential for Continual Prostate MRI Segmentatio." ArXiv (2024...