AdaMamba adds input-dependent frequency bases and a unified time-frequency forgetting gate to Mamba, yielding higher forecasting accuracy than prior methods on standard long-term time series benchmarks.
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3 Pith papers cite this work. Polarity classification is still indexing.
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cs.AI 3years
2026 3representative citing papers
An LLM-based agentic sampler over building knowledge graphs selects target-specific exogenous variables for zero-shot IoT forecasting, matching or beating trained baselines on three real buildings.
GeoDecider introduces a coarse-to-fine agentic workflow using LLMs for explainable lithology classification from well logs, combining a base classifier, tool-augmented reasoning, and geological refinement to outperform baselines on benchmarks.
citing papers explorer
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AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
AdaMamba adds input-dependent frequency bases and a unified time-frequency forgetting gate to Mamba, yielding higher forecasting accuracy than prior methods on standard long-term time series benchmarks.
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TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting
An LLM-based agentic sampler over building knowledge graphs selects target-specific exogenous variables for zero-shot IoT forecasting, matching or beating trained baselines on three real buildings.
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GeoDecider: A Coarse-to-Fine Agentic Workflow for Explainable Lithology Classification
GeoDecider introduces a coarse-to-fine agentic workflow using LLMs for explainable lithology classification from well logs, combining a base classifier, tool-augmented reasoning, and geological refinement to outperform baselines on benchmarks.