Cover Image

TabChange: Precise Attribute Changes in Tabular Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dahal, Arjun, Lei, Yu, Kacker, Raghu N., Kuhn, Richard
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ABLE: Using Adversarial Pairs to Construct Local Models for Explaining Model Predictions
by: Khadka, Krishna, et al.
Published: (2025)

TabDPT: Scaling Tabular Foundation Models on Real Data
by: Ma, Junwei, et al.
Published: (2024)

TabKD: Tabular Knowledge Distillation through Interaction Diversity of Learned Feature Bins
by: Pereira, Shovon Niverd, et al.
Published: (2026)

TabGen-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation
by: Fang, Liancheng, et al.
Published: (2025)

TabArena: A Living Benchmark for Machine Learning on Tabular Data
by: Erickson, Nick, et al.
Published: (2025)

MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
by: Sinodinos, Dimitrios, et al.
Published: (2025)

TabKANet: Tabular Data Modeling with Kolmogorov-Arnold Network and Transformer
by: Gao, Weihao, et al.
Published: (2024)

TabINR: An Implicit Neural Representation Framework for Tabular Data Imputation
by: Ochs, Vincent, et al.
Published: (2025)

TabAttackBench: A Benchmark for Adversarial Attacks on Tabular Data
by: He, Zhipeng, et al.
Published: (2025)

DP-TabICL: In-Context Learning with Differentially Private Tabular Data
by: Carey, Alycia N., et al.
Published: (2024)

TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data
by: Cureton, Cormac, et al.
Published: (2026)

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
by: Qu, Jingang, et al.
Published: (2025)

TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data
by: Chen, Suiyao, et al.
Published: (2024)

MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
by: Wang, Zifeng, et al.
Published: (2023)

Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study
by: Panagiotou, Emmanouil, et al.
Published: (2024)

DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data
by: Habib, Al Zadid Sultan Bin, et al.
Published: (2026)

TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering
by: Habib, Al Zadid Sultan Bin, et al.
Published: (2024)

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting
by: Margeloiu, Andrei, et al.
Published: (2024)

TabSieve: Explicit In-Table Evidence Selection for Tabular Prediction
by: Wang, Yongyao, et al.
Published: (2026)

TabSurv: Adapting Modern Tabular Neural Networks to Survival Analysis
by: Kirpichenko, Stanislav, et al.
Published: (2026)

TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes
by: Khatiwada, Aamod, et al.
Published: (2024)

ConTextTab: A Semantics-Aware Tabular In-Context Learner
by: Spinaci, Marco, et al.
Published: (2025)

OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
by: Jiang, Dihong, et al.
Published: (2026)

VisTabNet: Adapting Vision Transformers for Tabular Data
by: Wydmański, Witold, et al.
Published: (2024)

Can TabPFN Compete with GNNs for Node Classification via Graph Tabularization?
by: Choi, Jeongwhan, et al.
Published: (2025)

ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection
by: Yoon, Sanghyu, et al.
Published: (2025)

TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2025)

MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains
by: Lee, Kyungeun, et al.
Published: (2025)

TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees
by: Panagiotou, Emmanouil, et al.
Published: (2025)

Tabular Data with Class Imbalance: Predicting Electric Vehicle Crash Severity with Pretrained Transformers (TabPFN) and Mamba-Based Models
by: Somvanshi, Shriyank, et al.
Published: (2025)

TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
by: Cai, Donghong, et al.
Published: (2026)

Measuring and Mitigating Bias for Tabular Datasets with Multiple Protected Attributes
by: Duong, Manh Khoi, et al.
Published: (2024)

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
by: Yang, Yazheng, et al.
Published: (2023)

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
by: Garg, Anurag, et al.
Published: (2025)

Noise Immunity in In-Context Tabular Learning: An Empirical Robustness Analysis of TabPFN's Attention Mechanisms
by: Hu, James, et al.
Published: (2026)

TabResFlow: A Normalizing Spline Flow Model for Probabilistic Univariate Tabular Regression
by: Madhusudhanan, Kiran, et al.
Published: (2025)

Fully Test-time Adaptation for Tabular Data
by: Zhou, Zhi, et al.
Published: (2024)

TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications
by: Salinas, David, et al.
Published: (2023)

TabDistill: Distilling Transformers into Neural Nets for Few-Shot Tabular Classification
by: Dissanayake, Pasan, et al.
Published: (2025)

Universal Embeddings of Tabular Data
by: Franz, Astrid, et al.
Published: (2025)