Cluster-based semantic chunking does not outperform fixed-size or recursive chunking for RAG on academic theses, and RAGAs faithfulness shows limited reliability in this setup.
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A pipeline combining LDA, Top2Vec, GPT-2, similarity analysis, and human evaluation extracts policy agendas from social media with reported good inter-rater agreement and cosine similarity scores.
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Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts
Cluster-based semantic chunking does not outperform fixed-size or recursive chunking for RAG on academic theses, and RAGAs faithfulness shows limited reliability in this setup.