Lilian Weng's blog post details methods for constructing open-domain question-answering (ODQA) systems, focusing on Transformer-based language models. The post distinguishes ODQA from reading comprehension by highlighting the absence of provided context for factual questions. It also discusses challenges in QA data fine-tuning, where test-set questions or answers may appear in training sets, potentially inflating performance metrics. AI
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RANK_REASON Blog post detailing research methods for building ODQA systems.
