arXiv Computation and Language

From Repetition to Recognition: Inductive Discovery of Disinformation Narratives

The paper introduces a three-tier evaluation framework—recovery, mining, and discovery—for unsupervised narrative label generation in disinformation datasets. It compares clustering-based and graph-community-based pipelines across seven datasets, finding that clustering can underrepresent prominent topics while graph methods produce many singletons that human annotators recognize as valid narratives. The authors release human-validated narrative candidate labels for the Climate Obstruction and PolyNarrative datasets to aid taxonomy development and dataset expansion.

arXiv Computation and Language

Sep 11

Characterizing Narrative Content in Web-scale LLM Pretraining Data

The paper presents a detailed examination of narrative elements—agency, setting, and events—within the Dolma web-scale pretraining corpus. Using a framework of 11 interpretable dimensions, the authors hand‑annotated 400 passages, expanded this to a 25,000‑passage LLM‑labeled dataset, and trained NarraBERT models to predict narrative features across 13 million passages, producing the NarraDolma dataset. The study reveals that narrative structure is measurable at scale and that narrative qualities vary unevenly across different data sources, topics, and formats, highlighting gaps in current data curation practices.

By Teagan Johnson, Elliott Ash, Andrew Piper, Maria Antoniak

llms

arXiv AI

Jun 18

Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey

arXiv:2602. 15851v2 Announce Type: replace-cross Abstract: Applications of narrative theories using large language models (LLMs) deliver promising methods in automatic story generation and understanding tasks.

By David Y. Liu, Aditya Joshi, Paul Dawson

llms nlp benchmarks

arXiv AI

Jun 6

Narrative Knowledge Weaver: Narrative-Centric Retrieval-Augmented Reasoning for Long-Form Text Understanding

arXiv:2606. 05724v1 Announce Type: cross Abstract: Long-form narrative QA requires reasoning over evolving story worlds rather than isolated passages: answers may depend on earlier goals, changing character states, social relations, causal triggers, temporal position, and later consequences.

By Qiuyu Tian, Fengyi Chen, Yiding Li, Youyong Kong, Fan Guo, Yuyao Li, Jinjing Shen, Zhijing Xie, Yiyun Luo, Xin Zhang, Yingce Xia, Zequn Liu

rag benchmarks

arXiv AI

Sep 10

LitSeg: Narrative-Aware Document Segmentation for Literary RAG

arXiv:2605.27156v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by incorporating external knowledge, particularly for long-tail do...

By Ruikang Zhang, Zhanni Chen, Yiqiao Cai, Qi Su

llms rag computer-vision fine-tuning efficiency benchmarks

arXiv AI

Jun 17

Do Large Language Models Always Tell The Same Stories?

arXiv:2606. 17350v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet the question of whether these models are capable of generating diverse outputs remains contested.

By Thennal DK, Hans Ole Hatzel

llms

arXiv AI

Jul 8

Narrative World Model: Narratology-Grounded Writer Memory for Long-Form Fiction

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

agents benchmarks

arXiv Computation and Language

3d ago

The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation

arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate stori...

By Advait Deshmukh, Nora Benedict, Melanie Walsh, Maria Antoniak

llms benchmarks

arXiv AI

Jul 24

Semi-Supervised Text-Attributed Graph Distillation

arXiv:2607. 20477v1 Announce Type: new Abstract: {\em Text-Attributed Graphs} (TAGs) have emerged as an expressive data model for integrating graph topology with rich textual semantics.

By Yurui Lai, Samir Moustafa, Renchi Yang, Tsz Nam Chan

llms efficiency benchmarks

arXiv Computation and Language

Sep 2

LOOMSUM:Weaving Quantitative and Narrative Evidence for Faithful Long Text-Table Summarization

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

nlp multimodal benchmarks

arXiv AI

Jul 7

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

arXiv:2605. 06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than explicit names.

By Yehudit Aperstein, Eden Moran, Alexander Apartsin

llms rag nlp fine-tuning benchmarks

arXiv Computation and Language

3d ago

SlopShape: Identifying AI-Generated Commercial Web Content

arXiv:2609.15369v1 Announce Type: new Abstract: Word-level detectors identify unedited AI-generated text almost perfectly, but the literature documents their brittleness under rewording, and a word-l...

By Jochen Madler (Sitefire)

llms

arXiv AI

Jun 18

Retell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story Retelling

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

llms nlp reinforcement-learning fine-tuning

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