3 citations · 10 across the 26 of their papers we have counts for
7 papers · 1 filter
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…
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…
Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs
Tien Dang, Viet Thanh Duy Nguyen, Minh Tuan Le +1
Biomedical Knowledge Graphs (BKGs) integrate diverse datasets to elucidate complex relationships within the biomedical field. Effective link prediction on these graphs can uncover…
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder
Khai Le-Duc, Phuc Phan, Tan-Hanh Pham +5
Multilingual automatic speech recognition (ASR) in the medical domain serves as a foundational task for various downstream applications such as speech translation, spoken language…
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…
Sentiment Reasoning for Healthcare
Khai-Nguyen Nguyen, Khai Le-Duc, Bach Phan Tat +3
Transparency in AI healthcare decision-making is crucial. By incorporating rationales to explain reason for each predicted label, users could understand Large Language Models (LLMs…
Real-time Speech Summarization for Medical Conversations
Khai Le-Duc, Khai-Nguyen Nguyen, Long Vo-Dang +1
In doctor-patient conversations, identifying medically relevant information is crucial, posing the need for conversation summarization. In this work, we propose the first deployabl…