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In the rapidly evolving field of natural language processing, the translation of linguistic descriptions into mathematical formulation of optimization problems presents a formidable challenge, demanding intricate understanding and processing capabilities from Large Language Models (LLMs).
A new polynomial-time algorithm for linear programming
Karmarkar, N. 1984 · 1984
Earlier work this paper cites.
The (Dantzig) simplex method for linear programming
Nash, J. C. 2000 · 2000
Earlier work this paper cites.
Language Models are Few-Shot Learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T. J.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2005
Earlier work this paper cites.
Training Deep Nets with Sublinear Memory Cost
Chen, T.; Xu, B.; Zhang, C.; and Guestrin, C. 2016 · 2016
Earlier work this paper cites.
Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2017 · 2017
Earlier work this paper cites.
Attention is All you Need
Vaswani, A.; Shazeer, N. M.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
Earlier work this paper cites.
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; rahman Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2019 · 2019
Earlier work this paper cites.
Training Verifiers to Solve Math Word Problems
Cobbe, K.; Kosaraju, V.; Bavarian, M.; Chen, M.; Jun, H.; Kaiser, L.; Plappert, M.; Tworek, J.; Hilton, J.; Nakano, R.; Hesse, C.; and Schulman, J. 2021 · 2021
Cited alongside, same era.
LoRA: Low-Rank Adaptation of Large Language Models
Hu, J. E.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; and Chen, W. 2021 · 2021
Cited alongside, same era.
Green algorithms: quantifying the carbon footprint of computation
Lannelongue, L.; Grealey, J.; and Inouye, M. 2021 · 2021
Cited alongside, same era.
Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization
Laskar, M. T. R.; Hoque, E.; and Huang, J. 2021 · 2021
Cited alongside, same era.
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Jain, N.; yeh Chiang, P.; Wen, Y.; Kirchenbauer, J.; Chu, H.-M.; Somepalli, G.; Bartoldson, B.; Kailkhura, B.; Schwarzschild, A.; Saha, A.; Goldblum, M.; Geiping, J.; and Goldstein, T. 2023 · 2023
Later among the works it cites.
Large Language Models for Supply Chain Optimization
Li, B.; Mellou, K.; qing Zhang, B.; Pathuri, J.; and Menache, I. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions
Ramamonjison, R.; Yu, T. T.; Li, R.; Li, H.; Carenini, G.; Ghaddar, B.; He, S.; Mostajabdaveh, M.; Banitalebi-Dehkordi, A.; Zhou, Z.; and Zhang, Y. 2023 · 2023
Later among the works it cites.
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Cited alongside, same era.
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Cited alongside, same era.
Touvron, H.; Martin, L.; Stone, K. R.; Albert, P.; Almahairi, A.; Babaei, Y.; Bashlykov, N.; Batra, S.; Bhargava, P.; Bhosale, S.; Bikel, D. M.; Blecher, L.; Ferrer, C. C.; Chen, M.; Cucurull, G.; Esiobu, D.; Fernandes, J.; Fu, J.; Fu, W.; Fuller, B.; Gao, C.; Goswami, V.; Goyal, N.; Hartshorn, A. S.; Hosseini, S.; Hou, R.; Inan, H.; Kardas, M.; Kerkez, V.; Khabsa, M.; Kloumann, I. M.; Korenev, A. V.; Koura, P. S.; Lachaux, M.-A.; Lavril, T.; Lee, J.; Liskovich, D.; Lu, Y.; Mao, Y.; Martinet, X.; Mihaylov, T.; Mishra, P.; Molybog, I.; Nie, Y.; Poulton, A.; Reizenstein, J.; Rungta, R.; Saladi, K.; Schelten, A.; Silva, R.; Smith, E. M.; Subramanian, R.; Tan, X.; Tang, B.; Taylor, R.; Williams, A.; Kuan, J. X.; Xu, P.; Yan, Z.; Zarov, I.; Zhang, Y.; Fan, A.; Kambadur, M.; Narang, S.; Rodriguez, A.; Stojnic, R.; Edunov, S.; and Scialom, T. 2023 · 2023
Later among the works it cites.
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Later among the works it cites.
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