2 papers
cs.AI2026
Canonical Intermediate Representation for LLM-based optimization problem formulation and code generation
Zhongyuan Lyu, Shuoyu Hu, Lujie Liu +2
Automatically formulating optimization models from natural language descriptions is a growing focus in operations research, yet current LLM-based approaches struggle with the compo…
cs.CL2025
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Song Wang, Zihan Chen, Peng Wang +5
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or special…