UniAutoML: A Human-Centered Framework for Unified Discriminative and Generative AutoML with Large Language Models

arXiv:2410.12841 · cs.CL, cs.AI, cs.HC, cs.LG · Submitted 2024-10-09 · Read on arXiv

cs.CL, cs.AI, cs.HC, cs.LG

Submitted: 2024-10-09

Updated: 2024-10-18

Code: https://github.com/richarf22/UniAutoML

Terminology

• Accuracy — 25× in this paper · explained in 1 episode
• Fine-Tuning — 23× in this paper · explained in 5 episodes
• Diffusion Model — 22× in this paper · explained in 8 episodes
• Diffusion Models — 15× in this paper · explained in 6 episodes
• Large Language Model — 10× in this paper
• Interpretability — 9× in this paper · explained in 15 episodes
• Generative Model — 8× in this paper · explained in 2 episodes
• AUC — 7× in this paper · explained in 2 episodes
• Frustration — 7× in this paper · explained in 2 episodes
• Generative Models — 7× in this paper · explained in 2 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Feature Engineering — 4× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Bayesian Optimization — 3× in this paper · explained in 3 episodes
• Multimodal Dataset — 3× in this paper · explained in 2 episodes
• Neural Architecture Search — 3× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Meta-learning — 2× in this paper · explained in 2 episodes
• Pairwise Comparisons — 2× in this paper · explained in 2 episodes
• Shopee-Price Match Guarantee — 2× in this paper
• Adaptability — 1× in this paper · explained in 1 episode
• Cognitive Load — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Pre-trained Transformer — 1× in this paper
• Institutional Review Board — 1× in this paper
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Photo Aesthetics Ranking Archive — 1× in this paper
• Root Mean Squared Error — 1× in this paper
• System Usability Scale — 1× in this paper
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data
• An Open Source AutoML Benchmark
• LoRA: Low-Rank Adaptation of Large Language Models
• Language Models are Few-Shot Learners
• LLaMA: Open and Efficient Foundation Language Models
• LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
• Emergent Abilities of Large Language Models
• GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

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