Saved in:
| Main Authors: | Le, Hung, Venkatesh, Svetha |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.13162 |
| 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)
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)
by: Do, Dai, et al.
Published: (2025)
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)
Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
by: Le, Hung, et al.
Published: (2024)
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)
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)
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)
Large Language Models Prompting With Episodic Memory
by: Do, Dai, et al.
Published: (2024)
by: Do, Dai, et al.
Published: (2024)
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)
Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
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)
Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)
by: Ngo, Giang, et al.
Published: (2026)
Federated Domain Generalization with Latent Space Inversion
by: Palakkadavath, Ragja, et al.
Published: (2025)
by: Palakkadavath, Ragja, et al.
Published: (2025)
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)
Large Language Models for Imbalanced Classification: Diversity makes the difference
by: Nguyen, Dang, et al.
Published: (2025)
by: Nguyen, Dang, 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)
Revisiting the Dataset Bias Problem from a Statistical Perspective
by: Do, Kien, et al.
Published: (2024)
by: Do, Kien, et al.
Published: (2024)
Score-based Integrated Gradient for Root Cause Explanations of Outliers
by: Nguyen, Phuoc, et al.
Published: (2026)
by: Nguyen, Phuoc, et al.
Published: (2026)
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties
by: A V, Arun Kumar, et al.
Published: (2024)
by: A V, Arun Kumar, et al.
Published: (2024)
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)
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)
FedKRSO: Communication and Memory Efficient Federated Fine-Tuning of Large Language Models
by: Yang, Guohao, et al.
Published: (2026)
by: Yang, Guohao, et al.
Published: (2026)
Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
by: Nguyen, Tri Minh, et al.
Published: (2024)
by: Nguyen, Tri Minh, et al.
Published: (2024)
Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Models
by: Wang, Fei, et al.
Published: (2024)
by: Wang, Fei, et al.
Published: (2024)
Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence
by: Nguyen, Quoc Minh, et al.
Published: (2026)
by: Nguyen, Quoc Minh, et al.
Published: (2026)
Composite Concept Extraction through Backdooring
by: Ghosh, Banibrata, et al.
Published: (2024)
by: Ghosh, Banibrata, et al.
Published: (2024)
Self-Generative Adversarial Fine-Tuning for Large Language Models
by: Wu, Shiguang, et al.
Published: (2026)
by: Wu, Shiguang, et al.
Published: (2026)
Diversity in Large Language Models under Supervised Fine-Tuning
by: Klypa, Roman, et al.
Published: (2026)
by: Klypa, Roman, et al.
Published: (2026)
Decentralized Low-Rank Fine-Tuning of Large Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)
by: Ghiasvand, Sajjad, et al.
Published: (2025)
Sparse Gradient Compression for Fine-Tuning Large Language Models
by: Yang, David H., et al.
Published: (2025)
by: Yang, David H., et al.
Published: (2025)
ZO2: Scalable Zeroth-Order Fine-Tuning for Extremely Large Language Models with Limited GPU Memory
by: Wang, Liangyu, et al.
Published: (2025)
by: Wang, Liangyu, et al.
Published: (2025)
FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE
by: Le, Khiem, et al.
Published: (2025)
by: Le, Khiem, et al.
Published: (2025)
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
by: Pan, Rui, et al.
Published: (2024)
by: Pan, Rui, et al.
Published: (2024)
Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
by: Han, Bing, et al.
Published: (2025)
by: Han, Bing, et al.
Published: (2025)
Linearization Explains Fine-Tuning in Large Language Models
by: Afzal, Zahra Rahimi, et al.
Published: (2026)
by: Afzal, Zahra Rahimi, et al.
Published: (2026)
Dissecting Fine-Tuning Unlearning in Large Language Models
by: Hong, Yihuai, et al.
Published: (2024)
by: Hong, Yihuai, et al.
Published: (2024)
Security Vulnerability Detection with Multitask Self-Instructed Fine-Tuning of Large Language Models
by: Yang, Aidan Z. H., et al.
Published: (2024)
by: Yang, Aidan Z. H., et al.
Published: (2024)
Differentially Private Subspace Fine-Tuning for Large Language Models
by: Zheng, Lele, et al.
Published: (2026)
by: Zheng, Lele, et al.
Published: (2026)
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) -
Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
by: Nguyen, Manh, et al.
Published: (2025) -
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)