LM4OPT: Unveiling the potential of Large Language Models in formulating mathematical optimization problems
Author:
Affiliation:
1. School of Computing, Queen’s University, Kingston, Canada
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/03155986.2024.2388452
Reference31 articles.
1. AhmadiTeshnizi A Gao W Udell M. 2023. OptiMUS: optimization modeling using MIP solvers and large language models. ArXiv abs/2310.06116
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3. Almazrouei E Alobeidli H Alshamsi A Cappelli A Cojocaru R Debbah M Étienne G Hesslow D Launay J Malartic Q et al. 2023. The Falcon Series of Open Language Models. arXiv:2311.16867
4. Brown TB Mann B Ryder N Subbiah M Kaplan J Dhariwal P Neelakantan A Shyam P Sastry G Askell A et al. 2020. Language models are few-shot learners. In: Advances in Neural Information Processing Systems (pp. 1877–1901). Curran Associates Inc..
5. Chen T Xu B Zhang C Guestrin C. 2016. Training deep nets with sublinear memory cost. ArXiv abs/1604.06174
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