4 papers · 1 filter
Koa-decision: Fast and Consistent Structured Decision Making with Generative LLMs
Shenghong Dai, Shiva Kumar Pentyala, Yingchi Liu +6
Industry applications often demand low-latency classification, yet current large language model (LLM) approaches remain poorly suited for latency-critical applications. Existing pr…
Statistical Convergence of Transformer Encoder-Accelerated Robust Reinforcement Learning
Suman Banerjee, Hiroyasu Tsukamoto
Obtaining the optimal action-value function in Markov decision processes is computationally intensive in large state--action spaces. In this study, we present statistically rigorou…
PalmBench: A Comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms
Yilong Li, Jingyu Liu, Hao Zhang +7
Deploying large language models (LLMs) locally on mobile devices is advantageous in scenarios where transmitting data to remote cloud servers is either undesirable due to privacy c…
Buffer-based Gradient Projection for Continual Federated Learning
Shenghong Dai, Jy-yong Sohn, Yicong Chen +5
Continual Federated Learning (CFL) is essential for enabling real-world applications where multiple decentralized clients adaptively learn from continuous data streams. A significa…