Publications
My academic research focuses on advancing machine learning, particularly in AI Safety, Efficient ML, and Speech Processing. Full list also on Google Scholar.
[1] Quy-Anh Dang, Chris Ngo, Truong-Son Hy. RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track. [pdf]
[2] Quy-Anh Dang, Chris Ngo. Selective Steering: Norm-Preserving Control Through Discriminative Layer Selection. Findings of the Association for Computational Linguistics: ACL 2026. [pdf]
[3] Quy-Anh Dang, Chris Ngo. Polyglot-Lion: Efficient Multilingual ASR for Singapore via Balanced Fine-Tuning of Qwen3-ASR. Proceedings of Multilinguality in the Era of Large Language Models @ ACL 2026. [pdf]
[4] Quy-Anh Dang, Chris Ngo, Truong-Son Hy. RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models. Principled Design for Trustworthy AI: Interpretability, Robustness, and Safety across Modalities @ ICLR 2026. [pdf]
[5] Quy-Anh Dang, Chris Ngo. Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn’t. Logical and Symbolic Reasoning in Language Models @ AAAI 2026. [pdf]
[6] Quy-Anh Dang, Chris Ngo. MoD: A Distribution-Based Approach for Merging Large Language Models. LLM Merging Competition @ NeurIPS 2024. [pdf]
[7] Khai Le-Duc, Quy-Anh Dang, Tan-Hanh Pham, Truong-Son Hy. wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech. arXiv preprint. [pdf]