GenAI Projects

Learning never exhausts the mind
― Leonardo da Vinci

Collections

Name	URL
LLM terminology	Link
A Critical Look at MCP	Link
Ilya Rice: How I Won the Enterprise RAG Challenge	Link

Paper	Link	Preview
A Comprehensive Overview of Large Language Models	Click	ref
KBLaM: Knowledge Base augmented Language Model	Click
Retrieval-Augmented Generation for Large Language Models: A Survey	Click	ref
Revolutionizing Retrieval-Augmented Generation with Enhanced PDF Structure Recognition	Click
Optimizing RAG Techniques for Automotive Industry PDF Chatbots: A Case Study with Locally Deployed Ollama Models	Click
Google Prompt Engineering whitepaper		ref
Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time	Click
LLM Post-Training: A Deep Dive into Reasoning Large Language Models		ref
Decoder-Only or Encoder-Decoder? Interpreting Language Model as a Regularized Encoder-Decoder	Click
What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?	Click

LLM can be used to map schema from one format to another. This is useful for data migration and integration.

Resources	Link
blog (inspired by this blog)	Blog
paper (research paper on schema mapping)	ref

LLM can be used to generate features for machine learning models. This can save time and effort in the feature engineering process.

Resources	Link
paper (research paper on schema mapping)	ref
paper (research paper on schema mapping)	ref

LLM can be used to convert PDFs into structured data. This is useful for extracting information from unstructured documents.