Cover Image

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Long, Yunbo, Afonja, Tejumade, Hao, Guangya, Brintrup, Alexandra, Fritz, Mario
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

Topological Federated Clustering via Gravitational Potential Fields under Local Differential Privacy
by: Long, Yunbo, et al.
Published: (2025)

LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
by: Long, Yunbo, et al.
Published: (2025)

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators
by: Afonja, Tejumade, et al.
Published: (2024)

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation
by: Long, Yunbo, et al.
Published: (2025)

MathSE: Improving Multimodal Mathematical Reasoning via Self-Evolving Iterative Reflection and Reward-Guided Fine-Tuning
by: Chen, Jinhao, et al.
Published: (2025)

ConsistRM: Improving Generative Reward Models via Consistency-Aware Self-Training
by: Liang, Yu, et al.
Published: (2026)

Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs
by: Long, Yunbo, et al.
Published: (2026)

Entropy-Guided Data-Efficient Training for Multimodal Reasoning Reward Models
by: Yang, Shidong, et al.
Published: (2026)

SynDelay: A Synthetic Dataset for Delivery Delay Prediction
by: Xu, Liming, et al.
Published: (2025)

Random Walk Guided Hyperbolic Graph Distillation
by: Long, Yunbo, et al.
Published: (2025)

Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
by: Long, Yunbo, et al.
Published: (2025)

Debate as Reward: A Multi-Agent Reward System for Scientific Ideation via RL Post-Training
by: Salimi, Moein, et al.
Published: (2026)

Sampling for Quality: Training-Free Reward-Guided LLM Decoding via Sequential Monte Carlo
by: Markovic-Voronov, Jelena, et al.
Published: (2026)

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training
by: Xu, Yuanda, et al.
Published: (2026)

VeriTrace: Evolving Mental Models for Deep Research Agents
by: Zhao, Haolang, et al.
Published: (2026)

RiskPO: Risk-based Policy Optimization via Verifiable Reward for LLM Post-Training
by: Ren, Tao, et al.
Published: (2025)

Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design
by: Su, Xingyu, et al.
Published: (2025)

GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training
by: Cao, Yuan, et al.
Published: (2026)

Active Tabular Augmentation via Policy-Guided Diffusion Inpainting
by: Zhang, Zheyu, et al.
Published: (2026)

Efficient Process Reward Model Training via Active Learning
by: Duan, Keyu, et al.
Published: (2025)

Reward Model Overoptimisation in Iterated RLHF
by: Wolf, Lorenz, et al.
Published: (2025)

Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
by: Lee, Kyungeun, et al.
Published: (2024)

RewardHarness: Self-Evolving Agentic Post-Training
by: Zhang, Yuxuan, et al.
Published: (2026)

EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation
by: Long, Yunbo, et al.
Published: (2026)

Bootstrapped Mixed Rewards for RL Post-Training: Injecting Canonical Action Order
by: Gupta, Prakhar, et al.
Published: (2025)

A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning
by: Li, Mengqi, et al.
Published: (2025)

Improving Quantization with Post-Training Model Expansion
by: Franco, Giuseppe, et al.
Published: (2025)

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation
by: Afonja, Tejumade, et al.
Published: (2024)

Towards Biologically Plausible and Private Gene Expression Data Generation
by: Chen, Dingfan, et al.
Published: (2024)

Adversarial Training for Process Reward Models
by: Juneja, Gurusha, et al.
Published: (2025)

AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
by: Liu, Zihan, et al.
Published: (2024)

Chasing the Tail: Effective Rubric-based Reward Modeling for Large Language Model Post-Training
by: Zhang, Junkai, et al.
Published: (2025)

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

Interpreting Language Reward Models via Contrastive Explanations
by: Jiang, Junqi, et al.
Published: (2024)

Understanding Post-Training Structural Changes in Large Language Models
by: He, Xinyu, et al.
Published: (2025)

Post Training Quantization of Large Language Models with Microscaling Formats
by: Sharify, Sayeh, et al.
Published: (2024)

West-of-N: Synthetic Preferences for Self-Improving Reward Models
by: Pace, Alizée, et al.
Published: (2024)

GEM-T: Generative Tabular Data via Fitting Moments
by: Li, Miao, et al.
Published: (2025)

Self-Supervised Pre-Training for Precipitation Post-Processor
by: An, Sojung, et al.
Published: (2023)