6 papers · 1 filter
Multi-Rate Mixture of Experts for Accelerating Liquid Neural Network Training
Shilong Zong, Almuatazbellah Boker, Hoda Eldardiry
Multivariate time-series data often exhibit complex temporal dependencies, irregular sampling, and heterogeneous dynamics across multiple time scales, making accurate sequence mode…
Alleviating Community Fear in Disasters via Multi-Agent Actor-Critic Reinforcement Learning
Yashodhan D. Hakke, Almuatazbellah M. Boker, Lamine Mili +2
During disasters, cascading failures across power grids, communication networks, and social behavior amplify community fear and undermine cooperation. Existing cyber-physical-socia…
Accuracy, Memory Efficiency and Generalization: A Comparative Study on Liquid Neural Networks and Recurrent Neural Networks
Shilong Zong, Alex Bierly, Almuatazbellah Boker +1
This review aims to conduct a comparative analysis of liquid neural networks (LNNs) and traditional recurrent neural networks (RNNs) and their variants, such as long short-term mem…
Learning to Route LLMs from Bandit Feedback: One Policy, Many Trade-offs
Wang Wei, Tiankai Yang, Hongjie Chen +4
Efficient use of large language models (LLMs) is critical for deployment at scale: without adaptive routing, systems either overpay for strong models or risk poor performance from…
MMPlanner: Zero-Shot Multimodal Procedural Planning with Chain-of-Thought Object State Reasoning
Afrina Tabassum, Bin Guo, Xiyao Ma +2
Multimodal Procedural Planning (MPP) aims to generate step-by-step instructions that combine text and images, with the central challenge of preserving object-state consistency acro…
Efficient Model Selection for Time Series Forecasting via LLMs
Wang Wei, Tiankai Yang, Hongjie Chen +4
Model selection is a critical step in time series forecasting, traditionally requiring extensive performance evaluations across various datasets. Meta-learning approaches aim to au…