Cover Image

Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nguyen, Manh, Nguyen, Dung, Do, Dai, Venkatesh, Svetha, Le, Hung
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

Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
by: Le, Hung, et al.
Published: (2025)

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
by: Do, Dai, et al.
Published: (2025)

Beyond Surprise: Improving Exploration Through Surprise Novelty
by: Le, Hung, et al.
Published: (2023)

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
by: Le, Hung, et al.
Published: (2024)

Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory
by: Le, Hung, et al.
Published: (2024)

Continual Fine-Tuning of Large Language Models via Program Memory
by: Le, Hung, et al.
Published: (2026)

Multi-Reference Preference Optimization for Large Language Models
by: Le, Hung, et al.
Published: (2024)

Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024)

Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)

Distance Is All You Need: Radial Dispersion for Uncertainty Estimation in Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)

Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)

Revisiting the Dataset Bias Problem from a Statistical Perspective
by: Do, Kien, et al.
Published: (2024)

Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention
by: Nguyen, Manh, et al.
Published: (2026)

Large Language Models for Imbalanced Classification: Diversity makes the difference
by: Nguyen, Dang, et al.
Published: (2025)

Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)

GRAD: Graph-Retrieved Adaptive Decoding for Hallucination Mitigation
by: Nguyen, Manh, et al.
Published: (2025)

Reviving Error Correction in Modern Deep Time-Series Forecasting
by: Nguyen, Minh Hoang, et al.
Published: (2026)

Large Language Models Prompting With Episodic Memory
by: Do, Dai, et al.
Published: (2024)

Automatic Prompt Selection for Large Language Models
by: Do, Viet-Tung, et al.
Published: (2024)

Variational Flow Models: Flowing in Your Style
by: Do, Kien, et al.
Published: (2024)

Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
by: Le, Hung, et al.
Published: (2025)

Federated Domain Generalization with Latent Space Inversion
by: Palakkadavath, Ragja, et al.
Published: (2025)

Retrieval-augmented Decoding for Improving Truthfulness in Open-ended Generation
by: Nguyen, Manh, et al.
Published: (2025)

Score-based Integrated Gradient for Root Cause Explanations of Outliers
by: Nguyen, Phuoc, et al.
Published: (2026)

Leveraging Large Language Models for Information Verification -- an Engineering Approach
by: Hung, Nguyen Nang, et al.
Published: (2025)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret
by: Tran-The, Hung, et al.
Published: (2021)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
by: Tran-The, Hung, et al.
Published: (2019)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
by: Tran-The, Hung, et al.
Published: (2022)

Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026)

ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
by: Nguyen, Tri Minh, et al.
Published: (2026)

Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
by: Pham, Cuong, et al.
Published: (2025)

Optimizing Electric Vehicle Charging Station Placement Using Reinforcement Learning and Agent-Based Simulations
by: Nguyen, Minh-Duc, et al.
Published: (2025)

RL-Guided Data Selection for Language Model Finetuning
by: Jha, Animesh, et al.
Published: (2025)

Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration
by: Dao, Manh Cuong, et al.
Published: (2026)

Meta-Learning from Learning Curves for Budget-Limited Algorithm Selection
by: Nguyen, Manh Hung, et al.
Published: (2024)

Adaptive Layer-Wise Transformations for Post-Training Quantization of Large Language Models
by: Pham, Cuong, et al.
Published: (2025)

Graph Contrastive Learning via Spectral Graph Alignment
by: Nguyen, Manh
Published: (2025)

Finding the Trigger: Causal Abductive Reasoning on Video Events
by: Le, Thao Minh, et al.
Published: (2025)

Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models
by: Hoang, Dung Anh, et al.
Published: (2025)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
by: Tran-The, Hung, et al.
Published: (2020)