mlsanityData to 7 Oct 2026

EasyTPP: Towards Open Benchmarking Temporal Point Processes

arXiv 2307.08097 ↗First posted 16 Jul 2023cs.LGcited by 63

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Abstract (arXiv)

Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point processes (TPPs) have emerged as the most natural and competitive models, making a significant impact in both academic and application communities. Despite the emergence of many powerful models in recent years, there hasn't been a central benchmark for these models and future research endeavors. This lack of standardization impedes researchers and practitioners from comparing methods and reproducing results, potentially slowing down progress in this field. In this paper, we present EasyTPP, the first central repository of research assets (e.g., data, models, evaluation programs, documentations) in the area of event sequence modeling. Our EasyTPP makes several unique contributions to this area: a unified interface of using existing datasets and adding new datasets; a wide range of evaluation programs that are easy to use and extend as well as facilitate reproducible research; implementations of popular neural TPPs, together with a rich library of modules by composing which one could quickly build complex models. All the data and implementation can be found at https://github.com/ant-research/EasyTemporalPointProcess. We will actively maintain this benchmark and welcome contributions from other researchers and practitioners. Our benchmark will help promote reproducible research in this field, thus accelerating research progress as well as making more significant real-world impacts.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). Builds on 27 of its 48 references that are in the map. First posted on arXiv 16 Jul 2023.

Builds on

27 of 48 references.

References · 27

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2023GPT-4 Technical Reportcited by 18,132
  5. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
  6. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
  7. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  8. 2022Transformers in Time Series: A Surveycited by 489
  9. 2020Transformer Hawkes Processcited by 230
  10. 2019Intensity-Free Learning of Temporal Point Processescited by 138
  11. 2019Fully Neural Network based Model for General Temporal Point Processescited by 119
  12. 2017Modeling The Intensity Function Of Point Process Via Recurrent Neural Networkscited by 93
15 more
  1. 2020Neural Spatio-Temporal Point Processescited by 92
  2. 2021Transformer Embeddings of Irregularly Spaced Events and Their Participantscited by 90
  3. 2021Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformercited by 69
  4. 2022HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequencescited by 57
  5. 2020Open Benchmarking for Click-Through Rate Predictioncited by 53
  6. 2023Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoningcited by 44
  7. 2019Imputing Missing Events in Continuous-Time Event Streamscited by 43
  8. 2022Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processescited by 23
  9. 2017Tick: a Python library for statistical learning, with a particular emphasis on time-dependent modellingcited by 22
  10. 2020User-Dependent Neural Sequence Models for Continuous-Time Event Datacited by 17
  11. 2023Meta Temporal Point Processescited by 16
  12. 2020Visual Causality Analysis of Event Sequence Datacited by 12
  13. 2020Neural Datalog Through Time: Informed Temporal Modeling via Logical Specificationcited by 10
  14. 2020Point process models for sequence detection in high-dimensional neural spike trainscited by 10
  15. 2018PoPPy: A Point Process Toolbox Based on PyTorchcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 22; 2025: 18; 2026: 15.

63 papers.

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  1. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 109
  2. 2023Prompt-augmented Temporal Point Process for Streaming Event Sequencecited by 24
  3. 2024Decomposable Transformer Point Processescited by 15
  4. 2024HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting?cited by 11
  5. 2024Latent Logic Tree Extraction for Event Sequence Explanation from LLMscited by 9
  6. 2024Deep Continuous-Time State-Space Models for Marked Event Sequencescited by 9
  7. 2024CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecastingcited by 8
  8. 2024TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Modelscited by 8
  9. 2024EventFlow: Forecasting Temporal Point Processes with Flow Matchingcited by 8
  10. 2025DanmakuTPPBench: A Multi-modal Benchmark for Temporal Point Process Modeling and Understandingcited by 7
  11. 2025In-Context Learning of Temporal Point Processes with Foundation Inference Modelscited by 7
  12. 2024EBES: Easy Benchmarking for Event Sequencescited by 6
38 more
  1. 2025Parallel Token Prediction for Language Modelscited by 6
  2. 2024Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledgecited by 5
  3. 2025Neural Spatiotemporal Point Processes: Trends and Challengescited by 5
  4. 2024Federated Neural Nonparametric Point Processescited by 3
  5. 2024ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planningcited by 3
  6. 2023Deep Optimal Timing Strategies for Time Seriescited by 2
  7. 2023Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identificationcited by 2
  8. 2024Cumulative Hazard Function Based Efficient Multivariate Temporal Point Process Learningcited by 2
  9. 2025Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approachescited by 2
  10. 2025Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Modelcited by 2
  11. 2024Pretext Training Algorithms for Event Sequence Datacited by 1
  12. 2024ESQA: Event Sequences Question Answeringcited by 1
  13. 2024A Bayesian Mixture Model of Temporal Point Processes with Determinantal Point Process Priorcited by 1
  14. 2025ADiff4TPP: Asynchronous Diffusion Models for Temporal Point Processescited by 1
  15. 2025Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Taskscited by 1
  16. 2026HawkesNest: A Multi-Axis Synthetic Benchmark for Spatiotemporal Pattern Complexitycited by 1
  17. 2023Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inferencecited by 0
  18. 2023Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adaptercited by 0
  19. 2023GMTR: Graph Matching Transformerscited by 0
  20. 2023DarkShot: Lighting Dark Images with Low-Compute and High-Qualitycited by 0
  21. 2024TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processingcited by 0
  22. 2024TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networkscited by 0
  23. 2024T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Imagecited by 0
  24. 2024Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithmscited by 0
  25. 2024Towards General Deepfake Detection with Dynamic Curriculumcited by 0
  26. 2024Attr-Int: A Simple and Effective Entity Alignment Framework for Heterogeneous Knowledge Graphscited by 0
  27. 2024Marked Temporal Bayesian Flow Point Processescited by 0
  28. 2025Towards Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospectscited by 0
  29. 2025Looking around you: external information enhances representations for event sequencescited by 0
  30. 2025Prediction of Clinical Complication Onset using Neural Point Processescited by 0
  31. 2025Uncovering Social Network Activity Using Joint User and Topic Interactioncited by 0
  32. 2025Mask6D: Masked Pose Priors For 6D Object Pose Estimationcited by 0
  33. 2025Edge Selection for the Effective use of Piecewise-Constant Distributions as Neural Network Outputs for Event Predictioncited by 0
  34. 2025MOCHA: Discovering Multi-Order Dynamic Causality in Temporal Point Processescited by 0
  35. 2025Speculative Sampling for Parametric Temporal Point Processescited by 0
  36. 2025Addressing Mark Imbalance in Integration-free Neural Marked Temporal Point Processescited by 0
  37. 2025Benchmark Datasets for Lead-Lag Forecasting on Social Platformscited by 0
  38. 2026From Hawkes Processes to Attention: Time-Modulated Mechanisms for Event Sequencescited by 0

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