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Introduction

1. Introduction: LLM in the Age of AI

LLM Foundations

2. Language Models
3. Early Neural Language Models
4. Word Embeddings
5. Transformers
6. BERT
7. Seq2Seq: T5 and BART
8. GPT Series

LLM Architectures

9. LLM Architectures Fundamentals
10. MoE Sparse Architectures (WIP)

LLM Training

11. LLM Training Fundamentals
12. LLM Finetuning
13. LLM Alignement and Preference Learning
14. LLM Reasoning
15. LLM Training Acceleration (WIP)
16. *Reinforcement Learning Essentials

LLM Case Studies

17. DeepSeek Series
18. Llama Series

LLM Inference

19. Decoding
20. Inference Acceleration (WIP)

Prompting

21. Basic Prompting
22. Advanced Prompting Techniques

Text Embedding

23. Text Embedding Fundamentals
24. LLM Text Embedding

Vision LLM

25. Multimodality fundamentals
26. Vision Language Pretraining

Application in Information Retrieval and RAG

27. Information Retrieval and Sparse Retrieval
28. Information Retrieval and Dense Models
29. Application of LLM in IR (WIP)
30. Conversational IR (WIP)
31. RAG
32. Advanced RAG (WIP)

Multimodality fundamentals

25. Multimodality fundamentals#

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24. LLM Text Embedding

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26. Vision Language Pretraining

By Yuguang Yang

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