LLM / Multimodal
1
REA (Reverse Engineer Anything)
2
Decision Model: Jev, Kev
3
LLM Attention (with Code)
4
KAMF : Kafka-A2A-MCP-Flink
5
Agent's Memory: Knowledge Graph Memory MCP Server, Memory OS of AI Agent
6
VLM : Models Summary (unfinished post: 0618 update)
7
Prompt Engineering
8
GraphRAG (Microsoft)
9
What's different? : Agent, Agentic AI, Multi-Agent, Agentic RAG
10
DeepSeek-V3
11
Meta-Chunking: Learning Efficient Text Segmentation via Logical Perception
12
RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation
13
🚶➡Generative Agents: Interactive Simulacra of Human Behavior
14
Entropix : Entropy Based Sampling and Parallel CoT Decoding
15
Speculative Decoding
16
Vision : Self-Attention vs. Cross-Attention
17
Semantic Entropy: Summary of Two Papers on LLM Hallucination Detection 😱
18
LLaMa 3.1
19
MoE, MoA
20
Merge algorithms
21
Key-Value caching
22
DocLLM: A layout-aware generative language model for multimodal document understanding
23
VLM : Architecture / Fusion Methods
24
VLM : Applications
25
LLaVA : Visual Instruction Tuning
26
LLaMa 3
27
Fine-tuning variations : RLHF/PPO, DPO, ORPO
28
RAG : Embedding Model, Reranking Model
29
RAG : Similarity search (Keyword Search, Semantic Search, Hybrid Search)
30
RAG : Query Transformation/ Query Routing
31
RAG(Retrieval-Augmented Generation)
32
Mistral 7B
33
LLAMA 2: Open Foundation and Fine-Tuned Chat Models
34
Quentization basic
35
PEFT : Parameter-Efficient Finetuning methods
36
About Fine-tuning
37
LLM Architecture
38
Multimodal Learning with Transformers : A Survey
39
ㅡ
Natural Language Processing
Natural Language Processing and Linguistics
Machine Learning, Deep Learning
