1 citations · 1 across the 5 of their papers we have counts for
5 papers
Use ADAS Data to Predict Near-Miss Events: A Group-Based Zero-Inflated Poisson Approach
Xinbo Zhang, Montserrat Guillen, Lishuai Li +2
Driving behavior big data leverages multi-sensor telematics to understand how people drive and powers applications such as risk evaluation, insurance pricing, and targeted interven…
TADT-CSA: Temporal Advantage Decision Transformer with Contrastive State Abstraction for Generative Recommendation
Xiang Gao, Tianyuan Liu, Yisha Li +5
With the rapid advancement of Transformer-based Large Language Models (LLMs), generative recommendation has shown great potential in enhancing both the accuracy and semantic unders…
Reinforce Lifelong Interaction Value of User-Author Pairs for Large-Scale Recommendation Systems
Yisha Li, Lexi Gao, Jingxin Liu +4
Recommendation systems (RS) help users find interested content and connect authors with their target audience. Most research in RS tends to focus either on predicting users' immedi…
FreshRetailNet-50K: A Stockout-Annotated Censored Demand Dataset for Latent Demand Recovery and Forecasting in Fresh Retail
Yangyang Wang, Jiawei Gu, Li Long +5
Accurate demand estimation is critical for the retail business in guiding the inventory and pricing policies of perishable products. However, it faces fundamental challenges from c…
Supervised Learning-enhanced Multi-Group Actor Critic for Live Stream Allocation in Feed
Jingxin Liu, Xiang Gao, Yisha Li +3
In the context of a short video & live stream mixed recommendation scenario, the live stream recommendation system (RS) decides whether to allocate at most one live stream into the…