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LLM / Multimodal

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

Dev Log

1 Web Auto crawling + Retrieval 🌐♾️ 2 Video Retrieval system 📽️ 3 OCR+RAG: End-to-End system (Vision Grid Transformer) 4 Daily AI report with Git Action 5 Streaming search system : Function calling based ReAct Agents 6 Search system : #ReACT #HITL #Multi-Agent 7 OCR+RAG: End-to-End system (YOLO) 8 Self-RAG + CRAG : Query Router | Reranker | Relevant Grader | Hallucination Grader | Answer Grader 9 한국어 PDF Parser / PDF OCR (layout detection + text extraction) 10 Advanced RAG 11 LLM Tuning / Merge 12 NER(Named Entity Recognition) 13 Sentiment Analysis 14 ㅡ

Natural Language Processing

1 Prompt-Based Learning 3 | P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks 2 Prompt-Based Learning 2 | P-tuniung: GPT Understands, Too 3 Prompt-Based Learning 1 | PET(Pattern Exploiting Training), iPET(Iterative Pattern Exploiting Training) 4 Language Models Summary(unfinished post) 5 DAPT-TAPT | Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks 6 BERT | Pre-training of Deep Bidirectional Transformers for Language Understanding 7 Transformer | Attention Is All You Need 8 Attention in sequence to sequence 9 Sequence to Sequence(Seq2Seq) 10 GloVe(Global Word Vectors) 11 FastText | Enriching Word Vectors with Subword Information 12 Word2vec | Skip-gram 13 Word2Vec(Sentimental Categorize);with code 14 Word2vec | CBOW(Continuous Bag Of Words Model) 15 NPLM(Neural Probabilistic Language Model) 16 Word embedding(Distributed Representation) 17 LSA(Latent Sematic Analysis) 18 How to represent words?( Word Vectors) 19 Tokenization;with code 20 Regular Expression;with code 21 NLP Basics;with code 22 What is Natural Language Processing(NLP)?

Natural Language Processing and Linguistics

1 Coreference Resolution | Speech and Language Processing(Daniel Jurafsky and James H. Martin, 2019) 2 Investigating BERT’s Knowledge of Language:Five Analysis Methods with NPIs(Warstadt et al.(2019)) 3 Assessing the ability of Transformer-based Neural Models to represent structurally unbounded dependencies(Da Costa.J et al.(2020)) 4 What does BERT learn about the structure of language?(Jawahar.G(2019)) 5 Contextual word representation 6 A Structural Probe for Finding Syntax in Word Representations(Hewitt.J(2019)) 7 Linguistic Knowledge and Transferability of Contextual Representations(Liu(2019)) 8 What Can Linguistics and Deep Learning Contribute to Each Other? (Linzen et al. (2019)) 9 ㅡ

Project Log

1 Project list 2 ㅡ

Machine Learning, Deep Learning

1 Linear Regression;with code 2 K-Means;with code 3 L1, L2 (Norm, Loss, Regularization) 4 Transfer Learning, Multi-task Learning, End-to-End deep learning

Linguistics | English

1 Long-Distance Dependency(LDD) 2 Conversation Analysis | Adjacency Pair: Action and Understanding 3 Conversation Analysis | Preference Structure 4 Conversation Analysis | Turn-Taking 5 Conversation Analysis | Conversation Analysis Methods 6 Conversation Analysis | Conversation Analysis 7 ㅡ

Linguistik | Germanistik

1 Textlinguistik 2 Pragmatik 3 Semantische Theoriebildung 4 Semantische Grundbegriffe 5 Attribute und syntaktische Einzelprobleme 6 Ergaenzungen und Angaben 7 Dependenz und Valenz 8 Traditionelle Syntaxanalyse 9 Wordbildung und Flexion 10 Morphologie 11 Phonetik und Phonologie 12 Semiotik 13 Sprache und Linguistik

Language

1 Deutsch | Wendung2 2 Deutsch | Wendung 3 Deutsch | Grammatik

ETC.

1 1234 2 Docker 3 Linux 4 Git | Commit Rebase 5 Git | Branch 6 Git | Repository 7 color test