arXiv:2607. 05577v1 Announce Type: new Abstract: Long-form fiction writers need memory that answers multi-hop questions about evolving story state: who knows a secret and when they learned it, whether an event preceded the narration that revealed it, whether a setup paid off, and how a relationship shifted.
By Mohammad Saifullah, Thomas Kornmaier, Taaha Kazi, Vasu Sharma, Aditya Sanjiv Kanade, Aanand Kumar Yadav
NS-ST-GraphRAG is a neuro‑symbolic spatio‑temporal GraphRAG framework designed to process long‑form literary narratives by integrating ontology‑guided extraction, deterministic constraint checking, dual temporal coordinates, spatial scene attributes, and dynamic sub‑graph retrieval. It selects the appropriate graph state based on the temporal and spatial scope of a query, grounding generated answers in traceable evidence. The authors also introduce Red‑Chamber‑QA, an open multi‑hop question‑answering benchmark for classical Chinese literature, and report that NS‑ST‑GraphRAG outperforms a frozen‑window baseline and a closed‑book model on a held‑out 120‑question split.
By Zheng Kui Lin
arXiv:2609.00241v1 Announce Type: new
Abstract: Long documents often distribute important information across extensive narrative passages and multiple tables, making faithful summarization particular...
By Meng Zhou, Wenhao You, Wei Yuan
arXiv:2607. 09328v2 Announce Type: replace-cross Abstract: Answering complex questions over long documents frequently requires integrating evidence that the source itself disperses naturally across distant passages.
By Zixin Chen, Peng Liu, Haobo Li, Rui Sheng, Jianhong Tu, Xiaodong Deng, Fei Huang, Kashun Shum, Dayiheng Liu, Huamin Qu
arXiv:2607. 09328v1 Announce Type: cross Abstract: Answering complex questions over long documents frequently requires integrating evidence that the source itself disperses naturally across distant passages.
By Zixin Chen, Peng Liu, Haobo Li, Rui Sheng, Jianhong Tu, Xiaodong Deng, Fei Huang, Kashun Shum, Dayiheng Liu, Huamin Qu
arXiv:2601. 17226v2 Announce Type: replace-cross Abstract: Counterfactual story retelling exposes LLM shortcomings in constrained narrative solution spaces where they can no longer rely on recalling memorised training data.
By David Y. Liu, Xanthe Muston, Dipankar Srirag, Aditya Joshi, Sebastian Sequoiah-Grayson