18 citations · 18 across the 4 of their papers we have counts for
4 papers · 1 filter
Preference Optimization for Combinatorial Optimization Problems
Mingjun Pan, Guanquan Lin, You-Wei Luo +4
Reinforcement Learning (RL) has emerged as a powerful tool for neural combinatorial optimization, enabling models to learn heuristics that solve complex problems without requiring…
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
Fuqiang Liu, Sicong Jiang, Luis Miranda-Moreno +2
Large Language Models (LLMs) have recently demonstrated significant potential in time series forecasting, offering impressive capabilities in handling complex temporal data. Howeve…
A Gentle Introduction and Tutorial on Deep Generative Models in Transportation Research
Seongjin Choi, Zhixiong Jin, Seung Woo Ham +2
Deep Generative Models (DGMs) have rapidly advanced in recent years, becoming essential tools in various fields due to their ability to learn complex data distributions and generat…
Communication-Aware Reinforcement Learning for Cooperative Adaptive Cruise Control
Sicong Jiang, Seongjin Choi, Lijun Sun
Cooperative Adaptive Cruise Control (CACC) plays a pivotal role in enhancing traffic efficiency and safety in Connected and Autonomous Vehicles (CAVs). Reinforcement Learning (RL)…