Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
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T-RAG: LESSONS FROM THE LLM TRENCHES
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T-RAG 2024.06
LLaVA: Visual Instruction Tuning
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LLaVA 2023.04
RAG: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
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RAG 2020.05
FLAN: Finetuned Language Models Are Zero-shot Learners
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FLAN 2021.09 github: https://github.com/google-research/FLAN
GPT-3: Language Models are Few-Shot Learners
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GPT-3 2020.05
GPT-2: Language Models are Unsupervised Multitask Learners
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GPT-1: Improving Language Understanding by Generative Pre-Training
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LLM: Improving Language Understanding by Generative Pre-Training (GPT-1)
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
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LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
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StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation