arXiv Machine Learning
FlowTSFM: Turning Encoder Depth into Quantile Transport
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StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting
arXiv:2607. 00197v1 Announce Type: new Abstract: Long-horizon multivariate time series forecasting (LTSF) remains challenging due to non-stationarity, regime shifts, and error accumulation.
arXiv AI
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FlowState: Sampling-Rate-Equivariant Time-Series Forecasting
arXiv:2508. 05287v3 Announce Type: replace-cross Abstract: Existing time series foundation models (TSFMs), often based on transformer variants, lack adaptability to different sampling rates, struggle with generalization across varying context and target lengths, and are computationally inefficient.
arXiv Machine Learning
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RecurrentGPT: Expressive Depth through Recurrent Modulation in Transformers
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Gated Recurrent Transformers: Expressive Depth through Recurrent Modulation
The paper introduces Gated Recurrent Transformers, a depth‑sharing architecture that brackets a single shared core with fixed prelude and coda blocks and uses a lightweight projection and element‑wise update gate to modulate recurrent updates. This design allows functional specialization across recurrences while reducing memory footprint. Experiments show that, under equal FLOPs or parameter budgets, the recurrent model matches or surpasses deeper GPT‑2 Small baselines, achieving similar or better accuracy with fewer parameters and lower peak decoding memory.
arXiv Machine Learning
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Gated Recurrent Transformers: Expressive Depth through Recurrent Modulation in Transformers
arXiv:2608.15062v3 Announce Type: replace-cross Abstract: Scaling transformer language models creates an inherent tension between expressivity and memory efficiency. While unique weights across layer...
arXiv Machine Learning
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GatedLinear: Adaptive Routing of Complementary Linear Bases for Time Series Forecasting
arXiv:2607. 09537v1 Announce Type: new Abstract: Time series forecasting requires models to capture diverse, often mutually exclusive, temporal dynamics, from smooth trend continuation to nonstationary drift and strict phase-aligned recurrence.