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The ability of Large Language Models (LLMs) to generate high-quality text and code has fuelled their rise in popularity.
“Metaheuristics in combinatorial optimization: Overview and conceptual comparison”
Christian Blum and Andrea Roli · 2003
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“Language Models are Few-Shot Learners”, 2020
Tom. Brown et al · 2005
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“Metaheuristics in combinatorial optimization”
Michel Gendreau and Jean-Yves Potvin · 2005
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“Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”, 2021
Patrick Lewis et al · 2005
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“Search trajectory networks of population-based algorithms in continuous spaces”
Gabriela Ochoa, Katherine. Malan and Christian Blum · 2020
Earlier work this paper cites.
“Pre-trained models for natural language processing: A survey”
XiPeng Qiu et al · 2020
Earlier work this paper cites.
“The Power of Scale for Parameter-Efficient Prompt Tuning”
Brian Lester, Rami Al-Rfou and Noah Constant · 2021
Earlier work this paper cites.
Pengfei Liu et al · 2021
Earlier work this paper cites.
“Search trajectory networks: A tool for analysing and visualising the behaviour of metaheuristics”
Gabriela Ochoa, Katherine. Malan and Christian Blum · 2021
Earlier work this paper cites.
“Zero-Shot Text-to-Image Generation”, 2021
Aditya Ramesh et al · 2021
Earlier work this paper cites.
“Prompt programming for large language models: Beyond the few-shot paradigm”
Laria Reynolds and Kyle McDonell · 2021
Earlier work this paper cites.
“Do Prompt-Based Models Really Understand the Meaning of their Prompts?”
Albert Webson and Ellie Pavlick · 2021
Earlier work this paper cites.
“Solving Quantitative Reasoning Problems with Language Models”, 2022
Aitor Lewkowycz et al · 2022
Earlier work this paper cites.
“Training language models to follow instructions with human feedback”, 2022
Long Ouyang et al · 2022
Earlier work this paper cites.
“Multitask Prompted Training Enables Zero-Shot Task Generalization”, 2022
Victor Sanh et al · 2022
Earlier work this paper cites.
“Investigating explainability of generative AI for code through scenario-based design”
Jiao Sun et al · 2022
Earlier work this paper cites.
“Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models”
Priyan Vaithilingam, Tianyi Zhang and Elena. Glassman · 2022
Cited alongside, same era.
“Emergent Abilities of Large Language Models”, 2022
Jason Wei et al · 2022
Cited alongside, same era.
“Large language models are human-level prompt engineers”
Yongchao Zhou et al · 2022
Cited alongside, same era.
“STNWeb: A new visualization tool for analyzing optimization algorithms”
Camilo Chacón Sartori, Christian Blum and Gabriela Ochoa · 2023
Cited alongside, same era.
“Search Trajectory Networks Meet the Web: A Web Application for the Visual Comparison of Optimization Algorithms”
Camilo Chacon-Sartori, Christian Blum and Gabriela Ochoa · 2023
Cited alongside, same era.
“Leveraging Large Language Models for the Generation of Novel Metaheuristic Optimization Algorithms”
Michal Pluhacek et al · 2023
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“Code Llama: Open foundation models for code”
Baptiste Rozière et al · 2023
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“Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL”, 2023
Hao Sun, Alihan Hüyük and Mihaela van Schaar · 2023
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“Text Classification via Large Language Models”, 2023
Xiaofei Sun et al · 2023
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“Gemini: A Family of Highly Capable Multimodal Models”, 2023
Gemini Team et al · 2023
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Philip Feldman, James. Foulds and Shimei Pan · 2023
Cited alongside, same era.
Lei Huang et al · 2023
Cited alongside, same era.
“Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2”, 2023
Hamish Ivison et al · 2023
Cited alongside, same era.
Albert. Jiang et al · 2023
Cited alongside, same era.
“Evaluating Open-Domain Question Answering in the Era of Large Language Models”, 2023
Ehsan Kamalloo, Nouha Dziri, Charles.. Clarke and Davood Rafiei · 2023
Cited alongside, same era.
“Large Language Models are Zero-Shot Reasoners”, 2023
Takeshi Kojima et al · 2023
Cited alongside, same era.
“Guiding Large Language Models via Directional Stimulus Prompting”, 2023
Zekun Li et al · 2023
Cited alongside, same era.
Hugo Touvron et al · 2023
Later among the works it cites.
“Attention Is All You Need”, 2023
Ashish Vaswani et al · 2023
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“Chain-of-Thought Prompting Elicits Reasoning in Large Language Models”, 2023
Jason Wei et al · 2023
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“A Survey on Multimodal Large Language Models”, 2023
Shukang Yin et al · 2023
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“Prompting Large Language Model for Machine Translation: A Case Study”, 2023
Biao Zhang, Barry Haddow and Alexandra Birch · 2023
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“Sentiment Analysis in the Era of Large Language Models: A Reality Check”, 2023
Wenxuan Zhang et al · 2023
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“Explainability for Large Language Models: A Survey”, 2023
Haiyan Zhao et al · 2023
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“Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena”, 2023
Lianmin Zheng et al · 2023
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Kaijie Zhu et al · 2023
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“Retrieval-Augmented Generation for Large Language Models: A Survey”, 2024
Yunfan Gao et al · 2024
Closest in time.
“A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends”, 2024
Zibin Zheng et al · 2024
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