NLP - 标签 - Finisky Garden

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NLP 标签

2022

11-09

漫谈 Knowledge Grounded Conversation

10-26

小菲陪您唠唠磕

10-17

WeLM: A Well-Read Pre-trained Language Model for Chinese 简读

10-14

LaMDA: Language Models for Dialog Applications 简读

10-10

Towards Boosting the Open-Domain Chatbot with Human Feedback 简读

10-08

Leveraging Similar Users for Personalized Language Modeling with Limited Data 简读

09-22

Long-Term Open-Domain Conversation 简读

09-13

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering 简读

09-11

Long Time No See! Open-Domain Conversation with Long-Term Persona Memory 简读

06-03

深度文本检索模型：DPR, PolyEncoders, DCBERT, ColBERT

05-13

LoRA: Low-Rank Adaptation of Large Language Models 简读

05-01

NLP中的Adapters是什么？

04-07

神经网络为什么可以表示语言模型

01-05

Scaling Laws for Neural Language Models简读

2021

12-14

NLP Prompt技术简介

11-25

Nucleus Sampling与文本生成中的不同解码策略比较

11-14

使用LineByLine数据集训练GPT

07-18

Autoencoding和Autoregressive的区别

2020

07-09

熵，交叉熵，KL散度公式与计算实例

07-03

TextCNN pytorch实现