Narratives

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25 papers in the last four weeks, up 92% on the four weeks before. 0.2% of all new papers.

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Latest papers 191

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NarrativeTrack: Evaluating Entity-Centric Reasoning for Narrative Understanding
Jan 3, 2026Hyeonjeong Ha, Jinjin Ge, Bo Feng +2Video Multimodal Large Language Models Narratives
Apple · University of Illinois Urbana-Champaign
EchoFoley: Event-Centric Hierarchical Control for Video Grounded Creative Sound Generation
Dec 31, 2025Bingxuan Li, Yiming Cui, Yicheng He +4Audio-Video Generation Narratives
University of Illinois Urbana-Champaign · 1ByteDance Intelligent Creation · University of California, Los Angeles +1
Elsewise: Authoring Open-ended Interactive Narrative with Possibility Space Visualization
Dec 21, 2025Yi Wang, John Joon Young Chung, Melissa Roemmele +6Narrative Generation Narratives
Midjourney San Francisco, CA, USA · Independent Researcher San Francisco, CA, USA · UC Berkeley Berkeley, CA, USA +3
Narrative Consolidation: Formulating a New Task for Unifying Multi-Perspective Accounts
Dec 19, 2025Roger A. Finger, Eduardo G. Cortes, Sandro J. Rigo +1Narratives Summarization
Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos São Leopoldo, Brazil
Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies
Sep 13, 2025Yuping Wu, Viktor Schlegel, Warren Del-Pinto +11Clinical Notes Privacy-Preserving Framework
Univeristy of Manchester · Imperial College London, Imperial Global Singapore · Khoo Teck Puat Hospital, Singapore +2
Towards AI-Assisted Research Writing: Benchmarking LLMs for AI/ML Introduction Generation
Aug 19, 2025Krishna Garg, Firoz Shaik, Sambaran Bandyopadhyay +1Ai-Assisted Writing Narratives
University of Illinois Chicago · Adobe Research
Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts
Aug 2, 2025Xianda Zheng, Zijian Huang, Meng-Fen Chiang +4LLM Reasoning Strategies Reasoning Skills
School of Computer Science, University of Auckland · Department of Electronics and Electrical Engineering, National Yang Ming Chiao Tung University · School of Computing and Information Systems, Singapore Management University +1
Modeling Story Expectations: A Generative Framework using LLMs
Dec 13, 2024Hortense Fong, George Gui, Bo YangNarrative Generation Narratives
Columbia Business School
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
Mar 18, 2024Ziyi Chen, Mengyuan Zhang, Mustafa Mohammed Ahmed +4Cardiac Electronic Health Records
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA · Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, USA · Division of Hematology & Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
Tinker Tales: A Tangible Dialogue System for Child-AI Co-Creative Storytelling
Date pendingNayoung Choi, Jiseung Hong, Peace Cyebukayire +2Narrative Generation Dialogue
Department of Computer Science, Emory University · Department of Computer Science, Carnegie Mellon University · School of Nursing, Emory University
Characterizing Narrative Content in Web-scale LLM Pretraining Data
Date pendingTeagan Johnson, Elliott Ash, Andrew Piper +1Narratives Large Language Model Pretraining
University of Colorado Boulder · ETH Zürich · McGill University

Jan 3, 2026, cs.CVJ/K move · Enter open · S save

NarrativeTrack: Evaluating Entity-Centric Reasoning for Narrative Understanding

Hyeonjeong Ha, Jinjin Ge, Bo Feng, Kaixin Ma+1

Apple · University of Illinois Urbana-Champaign

Video Multimodal Large Language Models Narratives

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Multimodal large language models (MLLMs) have achieved impressive progress in vision-language reasoning, yet their ability to understand temporally unfolding narratives in videos remains underexplored. True narrative understanding requires grounding who is doing what, when, and where, maintaining coherent entity representations across dynamic visual and temporal contexts. We introduce NarrativeTrack, the first benchmark to evaluate narrative understanding in MLLMs through fine-grained entity-centric reasoning. Unlike existing benchmarks limited to short clips or coarse scene-level semantics, we decompose videos into constituent entities and examine their continuity via a Compositional Reasoning Progression (CRP), a structured evaluation framework that progressively increases narrative complexity across three dimensions: entity existence, entity changes, and entity ambiguity. CRP challenges models to advance from temporal persistence to contextual evolution and fine-grained perceptual reasoning. A fully automated entity-centric pipeline enables scalable extraction of temporally grounded entity representations, providing the foundation for CRP. Evaluations of state-of-the-art MLLMs reveal that models fail to robustly track entities across visual transitions and temporal dynamics, often hallucinating identity under context shifts. Open-source general-purpose MLLMs exhibit strong perceptual grounding but weak temporal coherence, while video-specific MLLMs capture temporal context yet hallucinate entities' contexts. These findings uncover a fundamental trade-off between perceptual grounding and temporal reasoning, indicating that narrative understanding emerges only from their integration. NarrativeTrack provides the first systematic framework to diagnose and advance temporally grounded narrative comprehension in MLLMs.

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