4 papers
Graph Optimization Foundation Model: Tokenizing Graph via A Language-Model Paradigm
Yunhao Liang, Pujun Zhang, Yuan Qu +3
The pretrain-transfer paradigm, which underpins the success of large language models (LLMs), has demonstrated the immense power of creating foundation models that learn generalizab…
Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models
Liang Guo, Lin Shaochong, Shen Zuo-Jun Max +1
Deploying large language models (LLMs) for operations research (OR) tasks remains challenging because correctness depends on a coherent modeling process, not merely a correct final…
Machine Learning for Scheduling: A Paradigm Shift from Solver-Centric to Data-Centric Approaches
Anbang Liu, Shaochong Lin, Jingchuan Chen +2
Scheduling problems are a fundamental class of combinatorial optimization problems that underpin operational efficiency in manufacturing, logistics, and service systems. While oper…
Everyone Contributes! Incentivizing Strategic Cooperation in Multi-LLM Systems via Sequential Public Goods Games
Yunhao Liang, Yuan Qu, Jingyuan Yang +2
Coordinating multiple large language models (LLMs) to solve complex tasks collaboratively poses a fundamental trade-off between the computation costs and collective performance com…