3 citations · 4 across the 4 of their papers we have counts for
4 papers
Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities
Yimo Yan, Yejia Liao, Guanhao Xu +13
The rapid rise of Large Language Models (LLMs) is transforming traffic and transportation research, with significant advancements emerging between the years 2023 and 2025 -- a peri…
CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation
Guofeng Cui, Pichao Wang, Yang Liu +3
Large language models (LLMs) have shown great potential in natural language processing tasks, but their application to machine translation (MT) remains challenging due to pretraini…
Interpretable mixture of experts for time series prediction under recurrent and non-recurrent conditions
Zemian Ke, Haocheng Duan, Sean Qian
Non-recurrent conditions caused by incidents are different from recurrent conditions that follow periodic patterns. Existing traffic speed prediction studies are incident-agnostic…
Real-time system optimal traffic routing under uncertainties -- Can physics models boost reinforcement learning?
Zemian Ke, Qiling Zou, Jiachao Liu +1
System optimal traffic routing can mitigate congestion by assigning routes for a portion of vehicles so that the total travel time of all vehicles in the transportation system can…