2 papers
cs.AI2026
Execution-Verified Reinforcement Learning for Optimization Modeling
Runda Guan, Xiangqing Shen, Jiajun Zhang +3
Automating optimization modeling with LLMs is a promising path toward scalable decision intelligence, but existing approaches either rely on agentic pipelines built on closed-sourc…
cs.CL2024
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models
Jinliang Lu, Ziliang Pang, Min Xiao +3
The remarkable success of Large Language Models (LLMs) has ushered natural language processing (NLP) research into a new era. Despite their diverse capabilities, LLMs trained on di…