19 papers
Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
Tung Quoc Le, Anh Tuan Nguyen, Viet Anh Nguyen
Data-driven algorithm design automates hyperparameter tuning, but its statistical foundations remain limited because model performance can depend on hyperparameters in implicit and…
PDF Retrieval Augmented Question Answering
Thi Thu Uyen Hoang, Meenakshi Rajendran, Kun Zhang +2
This paper presents an advancement in Question-Answering (QA) systems using a Retrieval Augmented Generation (RAG) framework to enhance information extraction from PDF files. Recog…
Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards
Hieu Trung Nguyen, Bao Nguyen, Wenao Ma +3
Sampling efficiency is a key bottleneck in reinforcement learning with verifiable rewards. Existing group-based policy optimization methods, such as GRPO, allocate a fixed number o…
Retrospective Feature Estimation for Continual Learning
Nghia D. Nguyen, Hieu Trung Nguyen, Ang Li +3
The intrinsic capability to continuously learn a changing data stream is a desideratum of deep neural networks (DNNs). However, current DNNs suffer from catastrophic forgetting, wh…
Exploring Diverse Generation Paths via Inference-time Stiefel Activation Steering
Dongxuan Zhu, Ly Tran Ho Khanh, Andy Yat-Ming Cheung +2
Language models often default to a narrow set of high-probability outputs, leaving their generation paths homogeneous and prone to mode collapse. Sampling-based strategies inject r…
CGCE: Classifier-Guided Concept Erasure in Generative Models
Viet Nguyen, Vishal M. Patel
Recent advancements in large-scale generative models have enabled the creation of high-quality images and videos, but have also raised significant safety concerns regarding the gen…