6 papers
Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models
Miao Li, Hanyang Jiang, Sikai Cheng +6
Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) approaches. However, current decoding s…
Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedback
Wyame Benslimane, Tinghan Ye, Pascal Van Hentenryck +1
Decision-focused learning (DFL) trains predictive models by optimizing downstream decision quality rather than standalone prediction accuracy. For contextual linear optimization, m…
Paratransit Optimization with Constraint Programming: A Case Study in Savannah, Georgia
Liam Jagrowski, Kevin Dalmeijer, Tinghan Ye +1
Paratransit services are vital for individuals who cannot use fixed-route public transit, including those with disabilities. Optimizing these services is essential for transit agen…
Contextual Stochastic Optimization for Omnichannel Multi-Courier Order Fulfillment Under Delivery Time Uncertainty
Tinghan Ye, Sikai Cheng, Amira Hijazi +1
The paper studies a large-scale order fulfillment problem for a leading e-commerce company in the United States. The challenge involves selecting fulfillment centers and shipping c…
Conformal Predictive Distributions for Order Fulfillment Time Forecasting
Tinghan Ye, Amira Hijazi, Pascal Van Hentenryck
Accurate estimation of order fulfillment time is critical for e-commerce logistics, yet traditional rule-based approaches often fail to capture the inherent uncertainties in delive…
Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling
Jiawei Lu, Tinghan Ye, Wenbo Chen +1
Optimizing service schedules is pivotal to the reliable, efficient, and inclusive on-demand mobility. This pressing challenge is further exacerbated by the increasing needs of an a…