4 papers · 1 filter
Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents
Qingcan Kang, Liu Mingyang, Shixiong Kai +3
Long-horizon language agents accumulate observations, reasoning traces, and retrieved facts exceeding context windows, making memory retention a fundamental resource-allocation pro…
EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling
Qingcan Kang, Mingyang Liu, Xiaojin Fu +3
Automating optimization modeling from natural language with large language models (LLMs) faces two key challenges. First, training corpora lack structural diversity. Second, data g…
A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions
Ziyang Xiao, Jingrong Xie, Lilin Xu +15
By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires su…
Decision Information Meets Large Language Models: The Future of Explainable Operations Research
Yansen Zhang, Qingcan Kang, Wing Yin Yu +5
Operations Research (OR) is vital for decision-making in many industries. While recent OR methods have seen significant improvements in automation and efficiency through integratin…