Extractive Question

Extractive question answering (EQA) focuses on identifying the answer to a question within a given text, directly extracting the relevant portion. Current research emphasizes improving EQA's robustness across diverse domains and handling long documents, often employing large language models (LLMs) and retrieval-augmented generation (RAG) architectures. Challenges include accurately attributing answers to their sources, particularly in long documents, and mitigating biases or limitations in LLMs' generalization capabilities across different knowledge domains. Addressing these challenges is crucial for building more reliable and versatile question-answering systems with applications ranging from information retrieval to personalized assistance.