CoLoRSMamba steers AudioMamba using video CLS-guided conditional LoRA to adapt selective state-space parameters, outperforming baselines on audio-filtered NTU-CCTV and DVD subsets with 88.63% and 75.77% accuracy respectively.
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ReTAMamba adds reliability decay modeling and chronological weaving to Mamba for irregular clinical time series and reports 7.5-10% relative AUPRC gains on MIMIC-IV, eICU, and PhysioNet 2012.
STM3 is a new multiscale Mamba mixture-of-experts model with graph causal networks and contrastive routing that reports state-of-the-art results on 10 long-term spatio-temporal forecasting benchmarks.
citing papers explorer
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CoLoRSMamba: Conditional LoRA-Steered Mamba for Supervised Multimodal Violence Detection
CoLoRSMamba steers AudioMamba using video CLS-guided conditional LoRA to adapt selective state-space parameters, outperforming baselines on audio-filtered NTU-CCTV and DVD subsets with 88.63% and 75.77% accuracy respectively.
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ReTAMamba: Reliability-Aware Temporal Aggregation with Mamba for Irregular Clinical Time Series Prediction
ReTAMamba adds reliability decay modeling and chronological weaving to Mamba for irregular clinical time series and reports 7.5-10% relative AUPRC gains on MIMIC-IV, eICU, and PhysioNet 2012.
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STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction
STM3 is a new multiscale Mamba mixture-of-experts model with graph causal networks and contrastive routing that reports state-of-the-art results on 10 long-term spatio-temporal forecasting benchmarks.