mlsanityData to 14 Oct 2026

TALENT: A Tabular Analytics and Learning Toolbox

arXiv 2407.04057 ↗First posted 4 Jul 2024cs.LGcited by 52

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Abstract (arXiv)

Tabular data is one of the most common data sources in machine learning. Although a wide range of classical methods demonstrate practical utilities in this field, deep learning methods on tabular data are becoming promising alternatives due to their flexibility and ability to capture complex interactions within the data. Considering that deep tabular methods have diverse design philosophies, including the ways they handle features, design learning objectives, and construct model architectures, we introduce a versatile deep-learning toolbox called TALENT (Tabular Analytics and LEarNing Toolbox) to utilize, analyze, and compare tabular methods. TALENT encompasses an extensive collection of more than 20 deep tabular prediction methods, associated with various encoding and normalization modules, and provides a unified interface that is easily integrable with new methods as they emerge. In this paper, we present the design and functionality of the toolbox, illustrate its practical application through several case studies, and investigate the performance of various methods fairly based on our toolbox. Code is available at https://github.com/qile2000/LAMDA-TALENT.

Key facts. Cited by 52 papers in the map (data through 14 Oct 2026). Builds on 42 of its 74 references that are in the map. First posted on arXiv 4 Jul 2024.

Builds on

42 of 74 references.

References · 42

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
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  4. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  5. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,501
  6. 2016Wide & Deep Learning for Recommender Systemscited by 747
  7. 2021Revisiting Deep Learning Models for Tabular Datacited by 740
  8. 2017DeepFM: A Factorization-Machine based Neural Network for CTR Predictioncited by 676
  9. 2022TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Secondcited by 674
  10. 2019TabNet: Attentive Interpretable Tabular Learningcited by 648
  11. 2017Self-Normalizing Neural Networkscited by 598
  12. 2021Deep Neural Networks and Tabular Data: A Surveycited by 491
30 more
  1. 2020TabTransformer: Tabular Data Modeling Using Contextual Embeddingscited by 409
  2. 2017Deep & Cross Network for Ad Click Predictionscited by 393
  3. 2020BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learningcited by 371
  4. 2020DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systemscited by 327
  5. 2018AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networkscited by 320
  6. 2021SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Trainingcited by 319
  7. 2023When Do Neural Nets Outperform Boosted Trees on Tabular Data?cited by 223
  8. 2019Neural Oblivious Decision Ensembles for Deep Learning on Tabular Datacited by 203
  9. 2022On Embeddings for Numerical Features in Tabular Deep Learningcited by 186
  10. 2021Well-tuned Simple Nets Excel on Tabular Datasetscited by 151
  11. 2021NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learningcited by 88
  12. 2023TabR: Tabular Deep Learning Meets Nearest Neighbors in 2023cited by 74
  13. 2016Deep Learning over Multi-field Categorical Data: A Case Study on User Response Predictioncited by 67
  14. 2024Making Pre-trained Language Models Great on Tabular Predictioncited by 57
  15. 2021DANets: Deep Abstract Networks for Tabular Data Classification and Regressioncited by 50
  16. 2020Gradient Boosting Neural Networks: GrowNetcited by 46
  17. 2022T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interactioncited by 41
  18. 2024SwitchTab: Switched Autoencoders Are Effective Tabular Learnerscited by 38
  19. 2023Trompt: Towards a Better Deep Neural Network for Tabular Datacited by 36
  20. 2023ExcelFormer: A neural network surpassing GBDTs on tabular datacited by 34
  21. 2023TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specializationcited by 32
  22. 2024PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learningcited by 32
  23. 2024HyperFast: Instant Classification for Tabular Datacited by 22
  24. 2021PyTorch Tabular: A Framework for Deep Learning with Tabular Datacited by 21
  25. 2024BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Modelcited by 21
  26. 2023ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Datacited by 18
  27. 2022DNNR: Differential Nearest Neighbors Regressioncited by 11
  28. 2023GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Datacited by 11
  29. 2024Arithmetic Feature Interaction Is Necessary for Deep Tabular Learningcited by 8
  30. 2022Label Encoding for Regression Networkscited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 10; 2026: 41.

52 papers.

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  1. 2025A Closer Look at TabPFN v2: Understanding Its Strengths and Extending Its Capabilitiescited by 41
  2. 2025TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problemscited by 36
  3. 2025Representation Learning for Tabular Data: A Comprehensive Surveycited by 36
  4. 2026Beyond IID: How General Are Tabular Foundation Models, Really?cited by 20
  5. 2025Multimodal Tabular Reasoning with Privileged Structured Informationcited by 15
  6. 2026EXAONE Tabular 1.0 : Technical Reportcited by 10
  7. 2026From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detectioncited by 9
  8. 2025LLM Meeting Decision Trees on Tabular Datacited by 8
  9. 2026TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attentioncited by 8
  10. 2026LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligencecited by 8
  11. 2026ScoringBench: A Benchmark for Evaluating Tabular Foundation Models with Proper Scoring Rulescited by 6
  12. 2026Towards Universal Tabular Embeddings: A Benchmark Across Data Taskscited by 6
38 more
  1. 2026MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detectioncited by 5
  2. 2025Realistic Evaluation of TabPFN v2 in Open Environmentscited by 4
  3. 2026Interpretable Tabular Foundation Models via In-Context Kernel Regressioncited by 4
  4. 2026TACTICL: Task-Aware Compression of Tabular ICL Modelscited by 4
  5. 2025Make Still Further Progress: Chain of Thoughts for Tabular Data Leaderboardcited by 3
  6. 2025MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretrainingcited by 3
  7. 2026Exactly Computing do-Shapley Valuescited by 3
  8. 2026Distributional Regression with Tabular Foundation Models: Evaluating Probabilistic Predictions via Proper Scoring Rulescited by 3
  9. 2026Foundation Models for Credit Risk Prediction: A Game Changer?cited by 3
  10. 2026TabH2O: A Unified Foundation Model for Tabular Predictioncited by 3
  11. 2024TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Datacited by 2
  12. 2025Feature-aware Modulation for Learning from Temporal Tabular Datacited by 1
  13. 2025Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learningcited by 1
  14. 2026Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learningcited by 1
  15. 2026Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Modelscited by 1
  16. 2026High Performance, Low Reliability: Uncertainty Benchmarking for Tabular Foundation Modelscited by 1
  17. 2026Exploring Differences Between Tabular Enterprise Data and Public Benchmarkscited by 1
  18. 2026ARASH: Adaptive Retrieval And Shot Selection for Tabular Predictioncited by 1
  19. 2026GEAR: Generative Expansion and Real Anchoring for Two-Stage Distillation of Tabular Foundation Modelscited by 1
  20. 2026From Synthetic Priors to Model Behavior: Structural Coverage in Tabular Foundation Modelscited by 1
  21. 2026SALT-KG: A Benchmark for Semantics-Aware Learning on Enterprise Tablescited by 0
  22. 2026mtslearn: Machine Learning in Python for Medical Time Seriescited by 0
  23. 2026TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Modelscited by 0
  24. 2026Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trapcited by 0
  25. 2026Cross-Domain Feature Expansion for Tabular Medical Data via Knowledge Graphs Injectioncited by 0
  26. 2026The Importance of Encoder Choice:A Tabular-Image Studycited by 0
  27. 2026Tabular Numeric Stretch Transformationcited by 0
  28. 2026Lost in Aggregation: How Benchmarks Overlook Irreplaceable Model Strengthscited by 0
  29. 2026ClusterAttention: A training-free speedup of bidirectional attentioncited by 0
  30. 2026Xiaomi-TabLDM: A Tabular Foundation Model Technical Reportcited by 0
  31. 2026TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tablescited by 0
  32. 2026PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Modelscited by 0
  33. 2026What Do Tabular Foundation Models Compute In Context? In-Situ Representation Refinement through Attention-Gated Updatescited by 0
  34. 2026LoopICL: Looping a single transformer block to solve tabular taskscited by 0
  35. 2026Distillation of Tabular Foundation Models into Efficient Predictorscited by 0
  36. 2026GIST: Generator-state-Informed Supervision for Tabular Foundation Modelscited by 0
  37. 2026How Well Do Prior-Data Fitted Networks Amortize Bayesian Inference?cited by 0
  38. 2026Characterizing the Separability Gap in Prior-Data Fitted Networkscited by 0

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