Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Le, Hung, Do, Dai, Nguyen, Dung, Venkatesh, Svetha |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
by: Le, Hung, et al.
Published: (2024)
by: Le, Hung, et al.
Published: (2024)
Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)
by: Nguyen, Manh, et al.
Published: (2025)
Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory
by: Le, Hung, et al.
Published: (2024)
by: Le, Hung, et al.
Published: (2024)
SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
by: Do, Dai, et al.
Published: (2025)
by: Do, Dai, et al.
Published: (2025)
Continual Fine-Tuning of Large Language Models via Program Memory
by: Le, Hung, et al.
Published: (2026)
by: Le, Hung, et al.
Published: (2026)
Beyond Surprise: Improving Exploration Through Surprise Novelty
by: Le, Hung, et al.
Published: (2023)
by: Le, Hung, et al.
Published: (2023)
Multi-Reference Preference Optimization for Large Language Models
by: Le, Hung, et al.
Published: (2024)
by: Le, Hung, et al.
Published: (2024)
Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024)
by: Nguyen, Minh Hoang, et al.
Published: (2024)
Large Language Models Prompting With Episodic Memory
by: Do, Dai, et al.
Published: (2024)
by: Do, Dai, et al.
Published: (2024)
Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
Revisiting the Dataset Bias Problem from a Statistical Perspective
by: Do, Kien, et al.
Published: (2024)
by: Do, Kien, et al.
Published: (2024)
Large Language Models for Imbalanced Classification: Diversity makes the difference
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, et al.
Published: (2025)
Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)
by: Ngo, Giang, et al.
Published: (2026)
Finding the Trigger: Causal Abductive Reasoning on Video Events
by: Le, Thao Minh, et al.
Published: (2025)
by: Le, Thao Minh, et al.
Published: (2025)
Reviving Error Correction in Modern Deep Time-Series Forecasting
by: Nguyen, Minh Hoang, et al.
Published: (2026)
by: Nguyen, Minh Hoang, et al.
Published: (2026)
Bayesian Optimistic Optimisation with Exponentially Decaying Regret
by: Tran-The, Hung, et al.
Published: (2021)
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)
by: Tran-The, Hung, et al.
Published: (2019)
Federated Domain Generalization with Latent Space Inversion
by: Palakkadavath, Ragja, et al.
Published: (2025)
by: Palakkadavath, Ragja, et al.
Published: (2025)
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
by: Tran-The, Hung, et al.
Published: (2022)
by: Tran-The, Hung, et al.
Published: (2022)
Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
by: Le, Hung, et al.
Published: (2025)
by: Le, Hung, et al.
Published: (2025)
Score-based Integrated Gradient for Root Cause Explanations of Outliers
by: Nguyen, Phuoc, et al.
Published: (2026)
by: Nguyen, Phuoc, et al.
Published: (2026)
Variational Flow Models: Flowing in Your Style
by: Do, Kien, et al.
Published: (2024)
by: Do, Kien, et al.
Published: (2024)
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
by: Tran-The, Hung, et al.
Published: (2020)
by: Tran-The, Hung, et al.
Published: (2020)
Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention
by: Nguyen, Manh, et al.
Published: (2026)
by: Nguyen, Manh, et al.
Published: (2026)
Model-Based Reinforcement Learning Under Confounding
by: Venkatesh, Nishanth, et al.
Published: (2025)
by: Venkatesh, Nishanth, 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)
by: Hoang, Dung Anh, et al.
Published: (2025)
Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models
by: Pham, Cuong, et al.
Published: (2025)
by: Pham, Cuong, et al.
Published: (2025)
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime
by: Shilton, Alistair, et al.
Published: (2024)
by: Shilton, Alistair, et al.
Published: (2024)
Automatic Prompt Selection for Large Language Models
by: Do, Viet-Tung, et al.
Published: (2024)
by: Do, Viet-Tung, et al.
Published: (2024)
Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models
by: Le, Khiem, et al.
Published: (2026)
by: Le, Khiem, et al.
Published: (2026)
Adaptive Layer-Wise Transformations for Post-Training Quantization of Large Language Models
by: Pham, Cuong, et al.
Published: (2025)
by: Pham, Cuong, et al.
Published: (2025)
ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
by: Nguyen, Tri Minh, et al.
Published: (2026)
by: Nguyen, Tri Minh, et al.
Published: (2026)
Optimizing Electric Vehicle Charging Station Placement Using Reinforcement Learning and Agent-Based Simulations
by: Nguyen, Minh-Duc, et al.
Published: (2025)
by: Nguyen, Minh-Duc, et al.
Published: (2025)
GRAD: Graph-Retrieved Adaptive Decoding for Hallucination Mitigation
by: Nguyen, Manh, et al.
Published: (2025)
by: Nguyen, Manh, et al.
Published: (2025)
Distance Is All You Need: Radial Dispersion for Uncertainty Estimation in Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)
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)
by: Nguyen, Manh, et al.
Published: (2025)
Studying Large Language Model Behaviors Under Context-Memory Conflicts With Real Documents
by: Kortukov, Evgenii, et al.
Published: (2024)
by: Kortukov, Evgenii, et al.
Published: (2024)
Teaching Large Language Models to Reason with Reinforcement Learning
by: Havrilla, Alex, et al.
Published: (2024)
by: Havrilla, Alex, et al.
Published: (2024)
Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks?
by: Das, Payel, et al.
Published: (2025)
by: Das, Payel, et al.
Published: (2025)
Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026)
by: Nguyen, Huu Hiep, et al.
Published: (2026)
Similar Items
-
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
by: Le, Hung, et al.
Published: (2024) -
Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
by: Nguyen, Manh, et al.
Published: (2025) -
Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory
by: Le, Hung, et al.
Published: (2024) -
SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
by: Do, Dai, et al.
Published: (2025) -
Continual Fine-Tuning of Large Language Models via Program Memory
by: Le, Hung, et al.
Published: (2026)