RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models - 代码天地

RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

物联网 2023-08-22 17:54:33 阅读次数: 0

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转载自blog.csdn.net/c_cpp_csharp/article/details/132426853

RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models

RETRIEVAL MEETS LONG CONTEXT LARGE LANGUAGE MODELS

【论文阅读】REPLUG: Retrieval-Augmented Black-Box Language Models

Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in GEC翻译

Retrieval-Augmented Multimodal Language Modeling

【In-Context Learning】Meta-learning via Language Model In-context Tuning

Augmented Language Models（增强语言模型）

Augmented Large Language Models with Parametric Knowledge Guiding

REALM: Retrieval-Augmented Language Model Pre-Training

Retrieval-Augmented Diffusion Models for Time Series Forecasting

Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers

In-Context Learning玩法大全

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation

Learning to Prompt for Vision-Language Models

Meta-Learning and in-context Learning

Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey，2020

In-Context Learning中的示例选择及效果

SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing

【In-Context Learning】Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

论文解读：Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentati

论文解读: 2023-Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval

Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community

开放域问答论文阅读-Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augme

Factorized Hidden Variability Learning For Adaptation Of Short Duration Language Identification Models

【微调视觉-语言模型】Learning to Prompt for Vision-Language Models

clip:learning transferable visual models from natural language supervision

【ICLR 2022】Towards Continual Knowledge Learning of Language Models

CLIP : Learning Transferable Visual Models From Natural Language Supervision

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

MASSIVE EDITING FOR LARGE LANGUAGE MODELS VIA META LEARNING

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