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Lilin Xu

4 accepted papers

2026

DeepOR: A Deep Reasoning Foundation Model for Optimization Modeling

AAAI 2026technical

Optimization modeling plays a critical role in supporting optimal decision-making across various domains. Previous works have demonstrated that large language models (LLMs) tailored for optimization modeling have significantly automated and simplified this process. However, these models typically em

Cited by 0SourcePDFScholar
2025

A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions

IJCAI 2025

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 substantial expertise from operations research professionals. With the advent of large language models (LLMs), new opportu

Cited by 0SourcePDFScholar
2025

ContextAgent: Context-Aware Proactive LLM Agents with Open-world Sensory Perceptions

NeurIPS 2025poster

Recent advances in Large Language Models (LLMs) have propelled intelligent agents from reactive responses to proactive support. While promising, existing proactive agents either rely exclusively on observations from enclosed environments (e.g., desktop UIs) with direct LLM inference or employ rule-…

Cited by 0SourcecodeScholar
2024

Chain-of-Experts: When LLMs Meet Complex Operations Research Problems

ICLR 2024poster

Large language models (LLMs) have emerged as powerful techniques for various NLP tasks, such as mathematical reasoning and plan generation. In this paper, we study automatic modeling and programming for complex operation research (OR) problems, so as to alleviate the heavy dependence on domain exper…

Cited by 50SourcePDFScholar