Next-Event Prediction

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16 papers5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Narrative Lookahead in LLMs: Event-Level Decodability, Predictive Advantage, and Steering
Oct 13, 2026Donghoon Jung, Min Kim, Seojin Choi +2Next-Event Prediction Text Generation
School of Digital Humanities and Computational Social Sciences, KAIST, South Korea
Foundation Models for Event Prediction Across Heterogeneous Event Logs
Oct 13, 2026Fabian Spaeh, Sean Jaffe, Shandian Zhe +1Next-Event Prediction Predictive Process Monitoring
Celonis
NextMe-800: Anticipating Personal Behavior from Months of Egocentric Video
Oct 1, 2026Zhaoxu Meng, Yiming Sun, Mingyuan Gao +5Next-Action Prediction Egocentric Video Understanding
The University of Hong Kong · Tongji University
EHRAdapt: Adapting Pretrained Language Models to Electronic Health Records with Semantic Priors for Rare Clinical Events
Sep 27, 2026Andre R Goncalves, Vincent Liu, Priyadip RayDomain Adaptation for LLMs Long-Tail Learning
Lawrence Livermore National Laboratory · Kaiser Permanente
Universal Multi-Modal Traceformer: Integrating Heterogeneous Context for Process Event Prediction
Sep 21, 2026Fabian Spaeh, Jingxing Fang, Shandian Zhe +1Event Time Prediction Predictive Process Monitoring
Celonis
Probabilistic Forecasting of Business Process Executions with Neural Temporal Point Processes
Sep 18, 2026Jiaxin Yuan, Daniela Grigori, Han van der AaProbabilistic Forecasting Predictive Process Monitoring
Paris Dauphine University-PSL, Pl. du Maréchal de Lattre de Tassigny, 75016 Paris, France · University of Vienna, Universitätsring 1, 1010 Wien, Austria
Foresight-England: Development of a National-Scale Generative AI Model of Electronic Health Records for Medical Event Prediction across the COVID-19 Pandemic
Aug 17, 2026Simon Ellershaw, Christopher Tomlinson, Zeljko Kraljevic +6EHR Foundation Models Next-Event Prediction
Institute of Health Informatics, University College London, London, UK · Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK · King’s Institute for Artificial Intelligence, King’s College London, London, UK +13
ReDiTT: Retrieval Augmented Conditional Diffusion Transformers for Asynchronous Time Series
Jul 14, 2026Saiyue Lyu, Zhitian Zhang, Ruizhi Deng +1Irregular Time-Series Modeling Event Time Prediction
Department of Computer Science, University of British Columbia · Work done during an internship at RBC Borealis. · RBC Borealis
A Foundation Model for Multimodal Event Sequences in Financial Applications
Jul 10, 2026Nikita Rusakov, Vladislav Meshkov, Konstantin Zorin +4Financial Services Multimodal Pretraining
Sber Moscow, Russian Federation · Sber AI Lab Moscow, Russian Federation
Dynamic Prediction of Alternating Recurrent Events via Neural Network
Jun 29, 2026Abigail Loe, Susan Murry, Zhenke WuEvent Time Prediction Survival Analysis
Department of Mathematics, Statistics and Computer Science, Macalester College, Saint Paul, Minnesota, U.S.A. · Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, U.S.A.
Scaling Laws for Behavioral Foundation Models over User Event Sequences
Jun 3, 2026Rickard Brüel GabrielssonNext-Event Prediction Behavioral Foundation Models
Unbox AI
GLIDE: Graph-guided Leap Inference for Diffusion Estimation of Spatio-Temporal Point Processes
May 31, 2026Guanyu Zhou, Yao Liu, Yanglei Gan +5Event Time Prediction Temporal Point Processes
University of Electronic Science and Technology of China, Chengdu, China
Promoting Simple Agents: Ensemble Methods for Event-Log Prediction
Apr 23, 2026Benedikt Bollig, Matthias Függer, Thomas Nowak +1Next-Action Prediction Ensemble Learning
Université Paris-Saclay, CNRS, ENS Paris-Saclay, LMF, Gif-sur-Yvette, France · Institut Universitaire de France, Paris, France · Direction Générale de l’Armement, Paris, France
Stochastic Event Prediction via Temporal Motif Transitions
Mar 6, 2026İbrahim Bahadır Altun, Ahmet Erdem SarıyüceTemporal Link Prediction Next-Event Prediction
University at Buffalo
LOBERT: Generative AI Foundation Model for Limit Order Book Messages
Nov 16, 2025Eljas Linna, Kestutis Baltakys, Alexandros Iosifidis +1Quantitative Finance Time Series Forecasting
Data Science Research Centre Tampere University
Edge Selection for the Effective use of Piecewise-Constant Distributions as Neural Network Outputs for Event Prediction
Jul 29, 2025Kevin Doran, Tom BadenEvent Time Prediction Probabilistic Forecasting
School of Life Sciences, University of Sussex, UK · School of Engineering and Informatics, University of Sussex, UK · Institute of Ophthalmic Research, University of Tübingen, Germany

Oct 13, 2026J/K move · Enter open · S save

Narrative Lookahead in LLMs: Event-Level Decodability, Predictive Advantage, and Steering

Donghoon Jung, Min Kim, Seojin Choi, Songeun Chae+1

School of Digital Humanities and Computational Social Sciences, KAIST, South Korea

Next-Event Prediction Text Generation Language Model Probing Language Model Steering

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Do language models carry information about narrative events before writing them, and how far ahead? We examine narrative lookahead through salient, state-changing events rather than tokens or response-level attributes. We extract 23,355 LLM-annotated events from 2,000 stories generated by four open-weight LLMs, labeling them along three nonexclusive dimensions of change: within agents, between agents, and in the story world, with human validation on a subset. Event segmentation and plot-independent labels enable comparisons across stories at horizons measured in events rather than in tokens. At event ends, we probe hidden states for upcoming event types and compare predictions with text-only predictors using matched prefixes. Across four models, future event types are decodable above prevalence baselines for at least four subsequent events, but probes significantly outperform both primary text-only predictors only for the next event. In exploratory steering with OLMo-3.1-32B, a probe-derived direction shifts the proportion of the target event type in both intended directions at higher strengths. Our event-level approach links the prediction of future narrative developments to interventions that reshape subsequent event composition.