{"total":23,"rows":[{"id":"2207.12560","title":"AMLB: an AutoML Benchmark","created":"2022-07-25","cited_by_count":55,"area":null},{"id":"2404.00776","title":"PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning","created":"2024-03-31","cited_by_count":32,"area":null},{"id":"2212.14453","title":"Learning Multimodal Data Augmentation in Feature Space","created":"2022-12-29","cited_by_count":18,"area":null},{"id":"2505.18125","title":"TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields","created":"2025-05-23","cited_by_count":18,"area":null},{"id":"2605.13986","title":"TabPFN-3: Technical Report","created":"2026-05-13","cited_by_count":17,"area":null},{"id":"2407.02112","title":"A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data","created":"2024-07-02","cited_by_count":15,"area":null},{"id":"2408.00665","title":"AutoM3L: An Automated Multimodal Machine Learning Framework with Large Language Models","created":"2024-08-01","cited_by_count":13,"area":null},{"id":"2208.14417","title":"Fraud Dataset Benchmark and Applications","created":"2022-08-30","cited_by_count":7,"area":null},{"id":"2412.16243","title":"Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data","created":"2024-12-19","cited_by_count":7,"area":null},{"id":"2605.12292","title":"STRABLE: Benchmarking Tabular Machine Learning with Strings","created":"2026-05-12","cited_by_count":4,"area":null},{"id":"2403.00963","title":"Tree-Regularized Tabular Embeddings","created":"2024-03-01","cited_by_count":3,"area":null},{"id":"2506.20494","title":"Multimodal Representation Learning and Fusion","created":"2025-06-25","cited_by_count":3,"area":null},{"id":"2305.14083","title":"Counterfactual Augmentation for Multimodal Learning Under Presentation Bias","created":"2023-05-23","cited_by_count":2,"area":null},{"id":"2402.16105","title":"Towards Automated Knowledge Integration From Human-Interpretable Representations","created":"2024-02-25","cited_by_count":2,"area":null},{"id":"2605.10616","title":"MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image","created":"2026-05-11","cited_by_count":2,"area":null},{"id":"2206.08473","title":"A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features","created":"2022-06-16","cited_by_count":1,"area":null},{"id":"2311.04518","title":"Towards Democratizing AI: A Comparative Analysis of AI as a Service Platforms and the Open Space for Machine Learning Approach","created":"2023-11-08","cited_by_count":1,"area":null},{"id":"2410.01933","title":"TAEGAN: Generating Synthetic Tabular Data For Data Augmentation","created":"2024-10-02","cited_by_count":1,"area":null},{"id":"2609.21894","title":"LLMs as Feature Engineers for Text-and-Tabular Prediction","created":"2026-09-18","cited_by_count":1,"area":null},{"id":"2302.12139","title":"Automated Extraction of Fine-Grained Standardized Product Information from Unstructured Multilingual Web Data","created":"2023-02-23","cited_by_count":0,"area":null},{"id":"2501.10848","title":"Fake Advertisements Detection Using Automated Multimodal Learning: A Case Study for Vietnamese Real Estate Data","created":"2025-01-18","cited_by_count":0,"area":null},{"id":"2512.00298","title":"Challenges of Heterogeneity in Big Data: A Comparative Study of Classification in Large-Scale Structured and Unstructured Domains","created":"2025-11-29","cited_by_count":0,"area":null},{"id":"2605.20674","title":"Modular Multimodal Classification Without Fine-Tuning: A Simple Compositional Approach","created":"2026-05-20","cited_by_count":0,"area":null}],"next_cursor":null}