Saved in:
| Main Authors: | Xu, Tommy, Zhang, Zhitian, Sun, Xiangyu, Zung, Lauren Kelly, Hajimirsadeghi, Hossein, Mori, Greg |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.21807 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
You Need Reasoning to Learn Reasoning: The Limitations of Label-Free RL in Weak Base Models
by: Roy, Shuvendu, et al.
Published: (2025)
by: Roy, Shuvendu, et al.
Published: (2025)
Attention as an RNN
by: Feng, Leo, et al.
Published: (2024)
by: Feng, Leo, et al.
Published: (2024)
Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding
by: Gao, Chufan, et al.
Published: (2025)
by: Gao, Chufan, et al.
Published: (2025)
ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning
by: Lin, Xiaofeng, et al.
Published: (2026)
by: Lin, Xiaofeng, et al.
Published: (2026)
TabPFGen -- Tabular Data Generation with TabPFN
by: Ma, Junwei, et al.
Published: (2024)
by: Ma, Junwei, et al.
Published: (2024)
Reinforcing Numerical Reasoning in LLMs for Tabular Prediction via Structural Priors
by: Cai, Pengxiang, et al.
Published: (2025)
by: Cai, Pengxiang, et al.
Published: (2025)
Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
by: Liu, Qihao, et al.
Published: (2025)
by: Liu, Qihao, et al.
Published: (2025)
Radar: Fast Long-Context Decoding for Any Transformer
by: Hao, Yongchang, et al.
Published: (2025)
by: Hao, Yongchang, et al.
Published: (2025)
Uncertainty-Aware Tabular Prediction: Evaluating VBLL-Enhanced TabPFN in Safety-Critical Medical Data
by: Ramalingam, Madhushan
Published: (2025)
by: Ramalingam, Madhushan
Published: (2025)
Cog-Rethinker: Hierarchical Metacognitive Reinforcement Learning for LLM Reasoning
by: Sun, Zexu, et al.
Published: (2025)
by: Sun, Zexu, et al.
Published: (2025)
From Residuals to Reasons: LLM-Guided Mechanism Inference from Tabular Data
by: Rezaei, Mohammad R., et al.
Published: (2026)
by: Rezaei, Mohammad R., et al.
Published: (2026)
TableGPT-R1: Advancing Tabular Reasoning Through Reinforcement Learning
by: Yang, Saisai, et al.
Published: (2025)
by: Yang, Saisai, et al.
Published: (2025)
TabText: Language-Based Representations of Tabular Health Data for Predictive Modelling
by: Carballo, Kimberly Villalobos, et al.
Published: (2022)
by: Carballo, Kimberly Villalobos, et al.
Published: (2022)
Tree Cross Attention
by: Feng, Leo, et al.
Published: (2023)
by: Feng, Leo, et al.
Published: (2023)
MambaTab: A Plug-and-Play Model for Learning Tabular Data
by: Ahamed, Md Atik, et al.
Published: (2024)
by: Ahamed, Md Atik, et al.
Published: (2024)
TabNSA: Native Sparse Attention for Efficient Tabular Data Learning
by: Eslamian, Ali, et al.
Published: (2025)
by: Eslamian, Ali, et al.
Published: (2025)
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
by: Shi, Juntong, et al.
Published: (2024)
by: Shi, Juntong, et al.
Published: (2024)
Rethinking the Sampling Criteria in Reinforcement Learning for LLM Reasoning: A Competence-Difficulty Alignment Perspective
by: Kong, Deyang, et al.
Published: (2025)
by: Kong, Deyang, et al.
Published: (2025)
TabDDPM: Modelling Tabular Data with Diffusion Models
by: Kotelnikov, Akim, et al.
Published: (2022)
by: Kotelnikov, Akim, et al.
Published: (2022)
TabStruct: Measuring Structural Fidelity of Tabular Data
by: Jiang, Xiangjian, et al.
Published: (2025)
by: Jiang, Xiangjian, et al.
Published: (2025)
An Explainable Diagnostic Framework for Neurodegenerative Dementias via Reinforcement-Optimized LLM Reasoning
by: Zamai, Andrew, et al.
Published: (2025)
by: Zamai, Andrew, et al.
Published: (2025)
Were RNNs All We Needed?
by: Feng, Leo, et al.
Published: (2024)
by: Feng, Leo, et al.
Published: (2024)
Chart-RVR: Reinforcement Learning with Verifiable Rewards for Explainable Chart Reasoning
by: Sinha, Sanchit, et al.
Published: (2025)
by: Sinha, Sanchit, et al.
Published: (2025)
TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields
by: Arazi, Alan, et al.
Published: (2025)
by: Arazi, Alan, et al.
Published: (2025)
TabArena: A Living Benchmark for Machine Learning on Tabular Data
by: Erickson, Nick, et al.
Published: (2025)
by: Erickson, Nick, et al.
Published: (2025)
MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
by: Sinodinos, Dimitrios, et al.
Published: (2025)
by: Sinodinos, Dimitrios, et al.
Published: (2025)
Explainable LLM Unlearning Through Reasoning
by: Liao, Junfeng, et al.
Published: (2026)
by: Liao, Junfeng, et al.
Published: (2026)
TabDSR: Decompose, Sanitize, and Reason for Complex Numerical Reasoning in Tabular Data
by: Jiang, Changjiang, et al.
Published: (2025)
by: Jiang, Changjiang, et al.
Published: (2025)
VeriReason: Reinforcement Learning with Testbench Feedback for Reasoning-Enhanced Verilog Generation
by: Wang, Yiting, et al.
Published: (2025)
by: Wang, Yiting, et al.
Published: (2025)
Memory Efficient Neural Processes via Constant Memory Attention Block
by: Feng, Leo, et al.
Published: (2023)
by: Feng, Leo, et al.
Published: (2023)
TabChange: Precise Attribute Changes in Tabular Data
by: Dahal, Arjun, et al.
Published: (2026)
by: Dahal, Arjun, et al.
Published: (2026)
DP-TabICL: In-Context Learning with Differentially Private Tabular Data
by: Carey, Alycia N., et al.
Published: (2024)
by: Carey, Alycia N., et al.
Published: (2024)
Making Bias Non-Predictive: Training Robust LLM Reasoning via Reinforcement Learning
by: Wang, Qian, et al.
Published: (2026)
by: Wang, Qian, et al.
Published: (2026)
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
by: Long, Yunbo, et al.
Published: (2025)
by: Long, Yunbo, et al.
Published: (2025)
InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation
by: Si, Jacob, et al.
Published: (2024)
by: Si, Jacob, et al.
Published: (2024)
TabSieve: Explicit In-Table Evidence Selection for Tabular Prediction
by: Wang, Yongyao, et al.
Published: (2026)
by: Wang, Yongyao, et al.
Published: (2026)
MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
by: Wang, Zifeng, et al.
Published: (2023)
by: Wang, Zifeng, et al.
Published: (2023)
TabImpute: Universal Zero-Shot Imputation for Tabular Data
by: Feitelberg, Jacob, et al.
Published: (2025)
by: Feitelberg, Jacob, et al.
Published: (2025)
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
by: Qu, Jingang, et al.
Published: (2025)
by: Qu, Jingang, et al.
Published: (2025)
HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing
by: Du, Chengyu, et al.
Published: (2026)
by: Du, Chengyu, et al.
Published: (2026)
Similar Items
-
You Need Reasoning to Learn Reasoning: The Limitations of Label-Free RL in Weak Base Models
by: Roy, Shuvendu, et al.
Published: (2025) -
Attention as an RNN
by: Feng, Leo, et al.
Published: (2024) -
Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding
by: Gao, Chufan, et al.
Published: (2025) -
ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning
by: Lin, Xiaofeng, et al.
Published: (2026) -
TabPFGen -- Tabular Data Generation with TabPFN
by: Ma, Junwei, et al.
Published: (2024)