activity
20242026
collaborators

8 papers

cs.DB2026

From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement

Dinh-Khanh Pham, Quy-Anh Dang, Lam Mai Thanh +2

RDBMS (Relational Database Management System) databases face several limitations, including slow execution with multi-hop queries and a lack of explainability by graphical interpre…

cs.CL2026

Polyglot-Lion: Efficient Multilingual ASR for Singapore via Balanced Fine-Tuning of Qwen3-ASR

Quy-Anh Dang, Chris Ngo

We present Polyglot-Lion, a family of compact multilingual automatic speech recognition (ASR) models tailored for the linguistic landscape of Singapore, covering English, Mandarin,…

cs.LG2026

Selective Steering: Norm-Preserving Control Through Discriminative Layer Selection

Quy-Anh Dang, Chris Ngo

Despite significant progress in alignment, large language models (LLMs) remain vulnerable to adversarial attacks that elicit harmful behaviors. Activation steering techniques offer…

cs.CL2026

RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models

Quy-Anh Dang, Chris Ngo, Truong-Son Hy

As large language models (LLMs) become integral to safety-critical applications, ensuring their robustness against adversarial prompts is paramount. However, existing red teaming d…

cs.CL2025

RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search

Quy-Anh Dang, Chris Ngo, Truong-Son Hy

Large Language Models (LLMs) exhibit remarkable capabilities but are susceptible to adversarial prompts that exploit vulnerabilities to produce unsafe or biased outputs. Existing r…

cs.LG2025

Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't

Quy-Anh Dang, Chris Ngo

Enhancing the reasoning capabilities of large language models (LLMs) typically relies on massive computational resources and extensive datasets, limiting accessibility for resource…

cs.LG2024

MoD: A Distribution-Based Approach for Merging Large Language Models

Quy-Anh Dang, Chris Ngo

Large language models (LLMs) have enabled the development of numerous specialized, task-specific variants. However, the maintenance and deployment of these individual models presen…

cs.CL2024

wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech

Khai Le-Duc, Quy-Anh Dang, Tan-Hanh Pham +1

Knowledge graphs (KGs) enhance the performance of large language models (LLMs) and search engines by providing structured, interconnected data that improves reasoning and context-a…