Saved in:
| Main Authors: | Gorla, Aditya, Puduppully, Ratish |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.04031 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Chimera: State Space Models Beyond Sequences
by: Lahoti, Aakash, et al.
Published: (2025)
by: Lahoti, Aakash, et al.
Published: (2025)
An Empirical Comparison of Vocabulary Expansion and Initialization Approaches for Language Models
by: Mundra, Nandini, et al.
Published: (2024)
by: Mundra, Nandini, et al.
Published: (2024)
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
by: Gorla, Aditya, et al.
Published: (2025)
by: Gorla, Aditya, et al.
Published: (2025)
Improving Genomic Models via Task-Specific Self-Pretraining
by: Mupparapu, Sohan, et al.
Published: (2025)
by: Mupparapu, Sohan, et al.
Published: (2025)
Exploring Fine-Tuning for Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2026)
by: Tanna, Aditya, et al.
Published: (2026)
The Reasoning Lingua Franca: A Double-Edged Sword for Multilingual AI
by: Saji, Alan, et al.
Published: (2025)
by: Saji, Alan, et al.
Published: (2025)
Interpretability Illusions in the Generalization of Simplified Models
by: Friedman, Dan, et al.
Published: (2023)
by: Friedman, Dan, et al.
Published: (2023)
AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection
by: Singh, Aditya, et al.
Published: (2024)
by: Singh, Aditya, et al.
Published: (2024)
Breaking the Illusion: Consensus-Based Generative Mitigation of Adversarial Illusions in Multi-Modal Embeddings
by: Akbarian, Fatemeh, et al.
Published: (2025)
by: Akbarian, Fatemeh, et al.
Published: (2025)
Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
Tabular Foundation Model for Generative Modelling
by: Jiang, Xiangjian, et al.
Published: (2026)
by: Jiang, Xiangjian, et al.
Published: (2026)
VerityMath: Advancing Mathematical Reasoning by Self-Verification Through Unit Consistency
by: Han, Vernon Toh Yan, et al.
Published: (2023)
by: Han, Vernon Toh Yan, et al.
Published: (2023)
Distilling Tabular Foundation Models for Structured Health Data
by: Tanna, Aditya, et al.
Published: (2026)
by: Tanna, Aditya, et al.
Published: (2026)
Inference Time Context Sparsity: Illusion or Opportunity?
by: Joshi, Sahil, et al.
Published: (2026)
by: Joshi, Sahil, et al.
Published: (2026)
TabQL: In-Context Q-Learning with Tabular Foundation Models
by: Liu, Qisai, et al.
Published: (2026)
by: Liu, Qisai, et al.
Published: (2026)
Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion
by: Shankar, Aditya, et al.
Published: (2026)
by: Shankar, Aditya, et al.
Published: (2026)
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models
by: Shankar, Aditya, et al.
Published: (2024)
by: Shankar, Aditya, et al.
Published: (2024)
Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data
by: Zhao, Zilong, et al.
Published: (2021)
by: Zhao, Zilong, et al.
Published: (2021)
Towards Universal Debiasing for Language Models-based Tabular Data Generation
by: Li, Tianchun, et al.
Published: (2025)
by: Li, Tianchun, et al.
Published: (2025)
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
by: An, Ulzee, et al.
Published: (2025)
by: An, Ulzee, et al.
Published: (2025)
A Benchmark Dataset for Multimodal Prediction of Enzymatic Function Coupling DNA Sequences and Natural Language
by: Zhang, Yuchen, et al.
Published: (2024)
by: Zhang, Yuchen, et al.
Published: (2024)
The Illusion of Superposition? A Principled Analysis of Latent Thinking in Language Models
by: Rizvi-Martel, Michael, et al.
Published: (2026)
by: Rizvi-Martel, Michael, et al.
Published: (2026)
TabularQGAN: A Quantum Generative Model for Tabular Data
by: Bhardwaj, Pallavi, et al.
Published: (2025)
by: Bhardwaj, Pallavi, et al.
Published: (2025)
RiddleBench: A New Generative Reasoning Benchmark for LLMs
by: Halder, Deepon, et al.
Published: (2025)
by: Halder, Deepon, et al.
Published: (2025)
Are UFOs Driving Innovation? The Illusion of Causality in Large Language Models
by: Carro, María Victoria, et al.
Published: (2024)
by: Carro, María Victoria, et al.
Published: (2024)
TabularFM: An Open Framework For Tabular Foundational Models
by: Tran, Quan M., et al.
Published: (2024)
by: Tran, Quan M., et al.
Published: (2024)
Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN
by: Sidorenko, Andrey, et al.
Published: (2025)
by: Sidorenko, Andrey, et al.
Published: (2025)
TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2025)
by: Tanna, Aditya, et al.
Published: (2025)
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models
by: Wen, Xumeng, et al.
Published: (2023)
by: Wen, Xumeng, et al.
Published: (2023)
Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap
by: Tanna, Aditya, et al.
Published: (2026)
by: Tanna, Aditya, et al.
Published: (2026)
Orion-Bix: Bi-Axial Attention for Tabular In-Context Learning
by: Bouadi, Mohamed, et al.
Published: (2025)
by: Bouadi, Mohamed, et al.
Published: (2025)
TabuLa: Harnessing Language Models for Tabular Data Synthesis
by: Zhao, Zilong, et al.
Published: (2023)
by: Zhao, Zilong, et al.
Published: (2023)
UniPredict: Large Language Models are Universal Tabular Classifiers
by: Wang, Ruiyu, et al.
Published: (2023)
by: Wang, Ruiyu, et al.
Published: (2023)
How Well Does Your Tabular Generator Learn the Structure of Tabular Data?
by: Jiang, Xiangjian, et al.
Published: (2025)
by: Jiang, Xiangjian, et al.
Published: (2025)
Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality
by: Bouadi, Mohamed, et al.
Published: (2026)
by: Bouadi, Mohamed, et al.
Published: (2026)
A Note on Statistically Accurate Tabular Data Generation Using Large Language Models
by: Sidorenko, Andrey
Published: (2025)
by: Sidorenko, Andrey
Published: (2025)
Hierarchical Conditional Tabular GAN for Multi-Tabular Synthetic Data Generation
by: Ågren, Wilhelm, et al.
Published: (2024)
by: Ågren, Wilhelm, et al.
Published: (2024)
Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning
by: Bouadi, Mohamed, et al.
Published: (2025)
by: Bouadi, Mohamed, et al.
Published: (2025)
CTSyn: A Foundation Model for Cross Tabular Data Generation
by: Lin, Xiaofeng, et al.
Published: (2024)
by: Lin, Xiaofeng, et al.
Published: (2024)
Evaluating Generative Models for Tabular Data: Novel Metrics and Benchmarking
by: Herurkar, Dayananda, et al.
Published: (2025)
by: Herurkar, Dayananda, et al.
Published: (2025)
Similar Items
-
Chimera: State Space Models Beyond Sequences
by: Lahoti, Aakash, et al.
Published: (2025) -
An Empirical Comparison of Vocabulary Expansion and Initialization Approaches for Language Models
by: Mundra, Nandini, et al.
Published: (2024) -
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
by: Gorla, Aditya, et al.
Published: (2025) -
Improving Genomic Models via Task-Specific Self-Pretraining
by: Mupparapu, Sohan, et al.
Published: (2025) -
Exploring Fine-Tuning for Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2026)