From Zero-Shot to Expert: A Deep Dive into Retrieval Domain Adaptation

Overview

1. Introduction

Part 1: The Foundations of Relevance

1. Information Retrieval (IR) Fundamentals
2. Lexical vs. Semantic Search
3. Embeddings: The Language of Meaning

Part 2: The Architectural Spectrum of Modern Retrieval

1. Bi-Encoders: The Foundation of Scalable Semantic Search
2. Cross-Encoders: The Gold Standard for Precision Reranking
3. A Deep Dive into BM25: The Science of Statistical Relevance
4. SPLADE: Teaching a Lexical Retriever to Think Semantically
5. ColBERT: Fine-Grained Interaction for Semantic Precision

Part 3: Assembling the State-of-the-Art Pipeline

1. The Hybrid Retriever: A Spectrum of Understanding
2. Reciprocal Rank Fusion (RRF): The Democratic Ensemble
3. The Modern Retriever: A Visual Guide

Part 4: The Art and Science of Model Training

1. Key IR Evaluation Metrics
2. The BEIR Framework for Reproducibility Research
3. The Need for Domain Adaptation
4. The Engine of DAPT: A Deep Dive into Masked Language Modeling
5. Training the 'Teacher': Supervised Fine-Tuning for the Cross-Encoder
6. The Art of Mimicry: The Mechanics of Knowledge Distillation for Retrieval

Part 5: The Full Picture

1. Beyond Retrieval—The Role of Context Refinement

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