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Research questionHow can long-form RAG answer multi-hop questions across changing temporal, spatial, and relational contexts?In long narratives, supporting facts may be separated across chapters while the relationships among characters, events, and locations change over narrative time. Answers must combine these dependencies rather than retrieve isolated matching passages.
AI
Evaluation & Benchmarks
Information Retrieval
Natural Language Processing
Reasoning
Retrieval-Augmented Generation
Latest papersRecent research connected to this question, newest first.NS-ST-GraphRAG: Neuro-Symbolic Spatio-Temporal GraphRAG for Literary Knowledge ProcessingThe source studies classical Chinese literary narratives with spatio-temporal and relational question answering, using the Red-Chamber-QA benchmark with per-part evidence spans and deterministic shortcut controls. On a 120-question held-out split, it reports higher mechanical answer reproduction than a frozen-window baseline, but the reported comparison was not statistically significant and its prespecified constrained-category hypothesis was unsupported.research paper · Sep 4, 2026
Related questions
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