Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Yanjun, Zhou, Tian, Chen, Chao, Sun, Liang, Qian, Yi, Jin, Rong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization Approach
by: Chen, Chao, et al.
Published: (2023)
by: Chen, Chao, et al.
Published: (2023)
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting
by: Ma, Ziqing, et al.
Published: (2024)
by: Ma, Ziqing, et al.
Published: (2024)
Attention as Robust Representation for Time Series Forecasting
by: Niu, PeiSong, et al.
Published: (2024)
by: Niu, PeiSong, et al.
Published: (2024)
BeamVQ: Beam Search with Vector Quantization to Mitigate Data Scarcity in Physical Spatiotemporal Forecasting
by: Wang, Weiyan, et al.
Published: (2025)
by: Wang, Weiyan, et al.
Published: (2025)
PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
by: Sun, Tian, et al.
Published: (2025)
by: Sun, Tian, et al.
Published: (2025)
Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)
by: Hu, Yifan, et al.
Published: (2025)
VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers
by: Deng, Juncan, et al.
Published: (2024)
by: Deng, Juncan, et al.
Published: (2024)
Transformer-VQ: Linear-Time Transformers via Vector Quantization
by: Lingle, Lucas D.
Published: (2023)
by: Lingle, Lucas D.
Published: (2023)
CommVQ: Commutative Vector Quantization for KV Cache Compression
by: Li, Junyan, et al.
Published: (2025)
by: Li, Junyan, et al.
Published: (2025)
Integer-only Quantized Transformers for Embedded FPGA-based Time-series Forecasting in AIoT
by: Ling, Tianheng, et al.
Published: (2024)
by: Ling, Tianheng, et al.
Published: (2024)
VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation
by: Noravesh, Farshad, et al.
Published: (2026)
by: Noravesh, Farshad, et al.
Published: (2026)
Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting
by: Liu, Peiyuan, et al.
Published: (2024)
by: Liu, Peiyuan, et al.
Published: (2024)
ArcVQ-VAE: A Spherical Vector Quantization Framework with ArcCosine Additive Margin
by: Kim, Jaeyung, et al.
Published: (2026)
by: Kim, Jaeyung, et al.
Published: (2026)
Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
by: Yang, Linxiao, et al.
Published: (2026)
by: Yang, Linxiao, et al.
Published: (2026)
VARMA-Enhanced Transformer for Time Series Forecasting
by: Song, Jiajun, et al.
Published: (2025)
by: Song, Jiajun, et al.
Published: (2025)
LATST: Are Transformers Necessarily Complex for Time-Series Forecasting
by: Liang, Dizhen
Published: (2024)
by: Liang, Dizhen
Published: (2024)
SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting
by: Xu, Xiongxiao, et al.
Published: (2024)
by: Xu, Xiongxiao, et al.
Published: (2024)
VQ-DeepISC: Vector Quantized-Enabled Digital Semantic Communication with Channel Adaptive Image Transmission
by: Chen, Jianqiao, et al.
Published: (2025)
by: Chen, Jianqiao, et al.
Published: (2025)
VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization
by: Zhang, Yiwei, et al.
Published: (2024)
by: Zhang, Yiwei, et al.
Published: (2024)
Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs
by: Zhao, Taibiao, et al.
Published: (2025)
by: Zhao, Taibiao, et al.
Published: (2025)
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecasting
by: Guo, Yangyang, et al.
Published: (2024)
by: Guo, Yangyang, et al.
Published: (2024)
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
by: Ouyang, Pengpeng, et al.
Published: (2025)
by: Ouyang, Pengpeng, et al.
Published: (2025)
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization
by: Li, Siyuan, et al.
Published: (2025)
by: Li, Siyuan, et al.
Published: (2025)
Analytical Provisioning for Attention-FFN Disaggregated LLM Serving under Stochastic Workloads
by: Song, Chendong, et al.
Published: (2026)
by: Song, Chendong, et al.
Published: (2026)
Accurate and Efficient Multi-Channel Time Series Forecasting via Sparse Attention Mechanism
by: Gao, Lei, et al.
Published: (2026)
by: Gao, Lei, et al.
Published: (2026)
SEDformer: Event-Synchronous Spiking Transformers for Irregular Telemetry Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2026)
by: Zhou, Ziyu, et al.
Published: (2026)
Breaking the Context Bottleneck on Long Time Series Forecasting
by: Ma, Chao, et al.
Published: (2024)
by: Ma, Chao, et al.
Published: (2024)
Amplify Adjacent Token Differences: Enhancing Long Chain-of-Thought Reasoning with Shift-FFN
by: Xu, Yao, et al.
Published: (2025)
by: Xu, Yao, et al.
Published: (2025)
SDMixer: Sparse Dual-Mixer for Time Series Forecasting
by: Ao, Xiang
Published: (2026)
by: Ao, Xiang
Published: (2026)
Understanding the Role of Textual Prompts in LLM for Time Series Forecasting: an Adapter View
by: Niu, Peisong, et al.
Published: (2023)
by: Niu, Peisong, et al.
Published: (2023)
Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
by: Jin, Ming, et al.
Published: (2023)
by: Jin, Ming, et al.
Published: (2023)
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting
by: Yue, Wenzhen, et al.
Published: (2025)
by: Yue, Wenzhen, et al.
Published: (2025)
Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
by: Zhang, Jianqi, et al.
Published: (2026)
by: Zhang, Jianqi, et al.
Published: (2026)
UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation
by: Zhou, Hanzhang, et al.
Published: (2024)
by: Zhou, Hanzhang, et al.
Published: (2024)
Fredformer: Frequency Debiased Transformer for Time Series Forecasting
by: Piao, Xihao, et al.
Published: (2024)
by: Piao, Xihao, et al.
Published: (2024)
Why Do Transformers Fail to Forecast Time Series In-Context?
by: Zhou, Yufa, et al.
Published: (2025)
by: Zhou, Yufa, et al.
Published: (2025)
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
by: Lu, Jiecheng, et al.
Published: (2024)
by: Lu, Jiecheng, et al.
Published: (2024)
HAS-VQ: Hessian-Adaptive Sparse Vector Quantization for High-Fidelity LLM Compression
by: Khasia, Vladimer
Published: (2026)
by: Khasia, Vladimer
Published: (2026)
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)
by: Feng, Shibo, et al.
Published: (2025)
Nexus : An Agentic Framework for Time Series Forecasting
by: Das, Sarkar Snigdha Sarathi, et al.
Published: (2026)
by: Das, Sarkar Snigdha Sarathi, et al.
Published: (2026)
Similar Items
-
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization Approach
by: Chen, Chao, et al.
Published: (2023) -
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting
by: Ma, Ziqing, et al.
Published: (2024) -
Attention as Robust Representation for Time Series Forecasting
by: Niu, PeiSong, et al.
Published: (2024) -
BeamVQ: Beam Search with Vector Quantization to Mitigate Data Scarcity in Physical Spatiotemporal Forecasting
by: Wang, Weiyan, et al.
Published: (2025) -
PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
by: Sun, Tian, et al.
Published: (2025)