LLMs built on Transformer architectures face significant scaling challenges due to their quadratic complexity in sequence length when processing long-context inputs. Methods like Linear Attention models, State Space Models like…
RWKV-X Combines Sparse Attention and Recurrent Memory to Enable Efficient 1M-Token Decoding with Linear Complexity
