{"ID":2831695,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.07539","arxiv_id":"2512.07539","title":"FRWKV:Frequency-Domain Linear Attention for Long-Term Time Series Forecasting","abstract":"Traditional Transformers face a major bottleneck in long-sequence time series forecasting due to their quadratic complexity $(\\mathcal{O}(T^2))$ and their limited ability to effectively exploit frequency-domain information. Inspired by RWKV's $\\mathcal{O}(T)$ linear attention and frequency-domain modeling, we propose FRWKV, a frequency-domain linear-attention framework that overcomes these limitations. Our model integrates linear attention mechanisms with frequency-domain analysis, achieving $\\mathcal{O}(T)$ computational complexity in the attention path while exploiting spectral information to enhance temporal feature representations for scalable long-sequence modeling. Across eight real-world datasets, FRWKV achieves a first-place average rank. Our ablation studies confirm the critical roles of both the linear attention and frequency-encoder components. This work demonstrates the powerful synergy between linear attention and frequency analysis, establishing a new paradigm for scalable time series modeling. Code is available at this repository: https://github.com/yangqingyuan-byte/FRWKV.","short_abstract":"Traditional Transformers face a major bottleneck in long-sequence time series forecasting due to their quadratic complexity $(\\mathcal{O}(T^2))$ and their limited ability to effectively exploit frequency-domain information. Inspired by RWKV's $\\mathcal{O}(T)$ linear attention and frequency-domain modeling, we propose F...","url_abs":"https://arxiv.org/abs/2512.07539","url_pdf":"https://arxiv.org/pdf/2512.07539v2","authors":"[\"Qingyuan Yang\",\"Shizhuo Deng\",\"Dongyue Chen\",\"Da Teng\",\"Zehua Gan\"]","published":"2025-12-08T13:18:20Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[\"Transformer\"]","has_code":false,"code_links":[{"ID":606152,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2831695,"paper_url":"https://arxiv.org/abs/2512.07539","paper_title":"FRWKV:Frequency-Domain Linear Attention for Long-Term Time Series Forecasting","repo_url":"https://github.com/yangqingyuan-byte/FRWKV","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}