Large Language Models for the Automated Analysis of Optimization Algorithms

arXiv:2402.08472 · cs.AI · Submitted 2024-02-13 · Read on arXiv

cs.AI

Submitted: 2024-02-13

Updated: 2024-02-13

Comments: Submitted to the GECCO 2024 conference

Journal ref: GECCO 2024

DOI: 10.1145/3638529.3654086

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Clustering — 20× in this paper · explained in 2 episodes
• Explainability — 13× in this paper · explained in 3 episodes
• Prompt Engineering — 8× in this paper · explained in 4 episodes
• Hallucination — 6× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 6× in this paper · explained in 6 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Combinatorial Optimization — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes

Sources

• Language Models are Few-Shot Learners
• Trapping LLM Hallucinations Using Tagged Context Prompts
• Retrieval-Augmented Generation for Large Language Models: A Survey
• A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
• Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2
• Mistral 7B
• Evaluating Open-Domain Question Answering in the Era of Large Language Models
• Large Language Models are Zero-Shot Reasoners
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
• Solving Quantitative Reasoning Problems with Language Models
• LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models
• Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
• Chat2VIS: Fine-Tuning Data Visualisations using Multilingual Natural Language Text and Pre-Trained Large Language Models
• GPT-4 Technical Report
• Training language models to follow instructions with human feedback
• Zero-Shot Text-to-Image Generation
• Multitask Prompted Training Enables Zero-Shot Task Generalization
• Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
• Gemini: A Family of Highly Capable Multimodal Models
• Llama 2: Open Foundation and Fine-Tuned Chat Models

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