Publications (6)
From Beginner to Expert: Modeling Medical Knowledge into General LLMs
Qiang Li, Xiaoyan Yang, Haowen Wang +14
Recently, large language model (LLM) based artificial intelligence (AI) systems have demonstrated remarkable capabilities in natural language understanding and generation. However,…
Enhancing mmWave Radar Point Cloud via Visual-inertial Supervision
Cong Fan, Shengkai Zhang, Kezhong Liu +3
Complementary to prevalent LiDAR and camera systems, millimeter-wave (mmWave) radar is robust to adverse weather conditions like fog, rainstorms, and blizzards but offers sparse po…
GACE: Learning Graph-Based Cross-Page Ads Embedding For Click-Through Rate Prediction
Haowen Wang, Yuliang Du, Congyun Jin +5
Predicting click-through rate (CTR) is the core task of many ads online recommendation systems, which helps improve user experience and increase platform revenue. In this type of r…
Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
Haowen Wang, Tao Sun, Cong Fan +1
Modular and composable transfer learning is an emerging direction in the field of Parameter Efficient Fine-Tuning, as it enables neural networks to better organize various aspects…
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning
Congyun Jin, Ming Zhang, Xiaowei Ma +13
Recent advancements in Large Language Models (LLMs) and Large Multi-modal Models (LMMs) have shown potential in various medical applications, such as Intelligent Medical Diagnosis.…
OrchMoE: Efficient Multi-Adapter Learning with Task-Skill Synergy
Haowen Wang, Tao Sun, Kaixiang Ji +3
We advance the field of Parameter-Efficient Fine-Tuning (PEFT) with our novel multi-adapter method, OrchMoE, which capitalizes on modular skill architecture for enhanced forward tr…