69 citations · 172 across the 44 of their papers we have counts for
14 papers · 1 filter
FlexRouter: Learning Complementary Model Sets for Flexible LLM Routing
Wang Wei, Harry Yang, Tiankai Yang +6
Existing Large Language Model (LLM) routing methods score LLMs independently to select top- models. However, this ignores model correlations and enforces a rigid computational b…
Online Learning with LLM Experts from Limited Feedback
Wang Wei, Soumyabrata Pal, Koyel Mukherjee +4
We study adaptive routing of prompts to large language model (LLM) experts to maximize response quality in an online setting with limited feedback. We formulate it as a bandit prob…
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…