Cover Image

Towards Fair In-Context Learning with Tabular Foundation Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kenfack, Patrik, Kahou, Samira Ebrahimi, Aïvodji, Ulrich
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fairness Under Demographic Scarce Regime
by: Kenfack, Patrik Joslin, et al.
Published: (2023)

Adaptive Group Robust Ensemble Knowledge Distillation
by: Kenfack, Patrik, et al.
Published: (2024)

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
by: Gupta, Nikunj, et al.
Published: (2023)

Learning to Play Atari in a World of Tokens
by: Agarwal, Pranav, et al.
Published: (2024)

Locally Constrained Representations in Reinforcement Learning
by: Nath, Somjit, et al.
Published: (2022)

When Interpretability Is Unequally Distributed: Fairness in Hybrid Interpretable Models
by: Zare, Ziba Jabbar, et al.
Published: (2026)

Learning Multi-agent Multi-machine Tending by Mobile Robots
by: Abdalwhab, Abdalwhab, et al.
Published: (2024)

Cross-Layer Discrete Concept Discovery for Interpreting Language Models
by: Garg, Ankur, et al.
Published: (2025)

Vector Quantized Latent Concepts: A Scalable Alternative to Clustering-Based Concept Discovery
by: Yu, Xuemin, et al.
Published: (2026)

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation
by: Azimi, Rambod, et al.
Published: (2024)

Active In-Context Learning for Tabular Foundation Models
by: Treerath, Wilailuck, et al.
Published: (2026)

Handling Delay in Real-Time Reinforcement Learning
by: Anokhin, Ivan, et al.
Published: (2025)

Reinforcement Learning for Sequence Design Leveraging Protein Language Models
by: Subramanian, Jithendaraa, et al.
Published: (2024)

FairPFN: A Tabular Foundation Model for Causal Fairness
by: Robertson, Jake, et al.
Published: (2025)

Survey on AI Ethics: A Socio-technical Perspective
by: Mbiazi, Dave, et al.
Published: (2023)

TabQL: In-Context Q-Learning with Tabular Foundation Models
by: Liu, Qisai, et al.
Published: (2026)

Test-Time Collective Action: Proxy-Based Perturbations for Correcting Algorithmic Harms
by: Bhange, Meghana, et al.
Published: (2026)

VIP-COP: Context Optimization for Tabular Foundation Models
by: Chen, Yilong, et al.
Published: (2026)

TFMLinker: Universal Link Predictor by Graph In-Context Learning with Tabular Foundation Models
by: Liao, Tianyin, et al.
Published: (2026)

Interpretable Tabular Foundation Models via In-Context Kernel Regression
by: Miftachov, Ratmir, et al.
Published: (2026)

Prediction of Final Phosphorus Content of Steel in a Scrap-Based Electric Arc Furnace Using Artificial Neural Networks
by: Azzaz, Riadh, et al.
Published: (2024)

Empowering Clinicians with Medical Decision Transformers: A Framework for Sepsis Treatment
by: Rahman, Aamer Abdul, et al.
Published: (2024)

Towards Benchmarking Foundation Models for Tabular Data With Text
by: Mráz, Martin, et al.
Published: (2025)

Towards Understanding Layer Contributions in Tabular In-Context Learning Models
by: Balef, Amir Rezaei, et al.
Published: (2025)

Improving LLM Group Fairness on Tabular Data via In-Context Learning
by: Cherepanova, Valeriia, et al.
Published: (2024)

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

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses
by: Djilani, Mohamed, et al.
Published: (2025)

Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy
by: Solanki, Rushabh, et al.
Published: (2025)

LUCoS: Latent Unsupervised Context Selection for Tabular Foundation Models
by: Ipas, Oroel, et al.
Published: (2026)

TabularFM: An Open Framework For Tabular Foundational Models
by: Tran, Quan M., et al.
Published: (2024)

Towards Foundation Inference Models that Learn ODEs In-Context
by: Mauel, Maximilian, et al.
Published: (2025)

On Finetuning Tabular Foundation Models
by: Rubachev, Ivan, et al.
Published: (2025)

The Sandbox Environment for Generalizable Agent Research (SEGAR)
by: Hjelm, R Devon, et al.
Published: (2022)

Turning Tabular Foundation Models into Graph Foundation Models
by: Eremeev, Dmitry, et al.
Published: (2025)

Tabular Foundation Model for Generative Modelling
by: Jiang, Xiangjian, et al.
Published: (2026)

Risk In Context: Benchmarking Privacy Leakage of Foundation Models in Synthetic Tabular Data Generation
by: Byun, Jessup, et al.
Published: (2025)

GAMformer: Bridging Tabular Foundation Models and Interpretable Machine Learning
by: Mueller, Andreas, et al.
Published: (2024)

Early Stopping Tabular In-Context Learning
by: Küken, Jaris, et al.
Published: (2025)

Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists
by: Ly, Timothée, et al.
Published: (2024)

Robust Tabular Foundation Models
by: Peroni, Matthew, et al.
Published: (2025)