23 citations · 63 across the 23 of their papers we have counts for
26 papers
LogicTree-RAG: Logic Tree-guided Retrieval-Augmented Generation for Long-form Patent Drafting
Jiaqi Zhu, Naili Xing, Hexiang Pan +4
Long-form technical text generation underpins knowledge-intensive workflows, yet remains challenging for large language models (LLMs) due to the need for globally consistent logica…
FAgent: Financial Fusion of Agentic Intelligence for Multimodal Trading
Changshuo Liu, Yanzheng Jin, Shangfeng Cai +3
With increasingly diverse and heterogeneous information sources, effectively leveraging multimodal data is becoming pivotal for high-quality financial trading. Although recent adva…
SGN: A Similarity-based Generative Network for Data Generation under Distribution Shift
Jiaqi Zhu, Xincheng Chen, Yuncheng Wu +2
Generative models trained on a source domain often produce samples that are poorly aligned with shifted target domains, limiting their effectiveness for target-domain data augmenta…
From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics
Lingze Zeng, Shaofeng Cai, Changshuo Liu +3
Relational data stored in RDBMS is foundational to many real-world applications across domains such as e-commerce, finance, and sociality. While deep neural networks (DNNs) have ac…
Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation
Jiaqi Zhu, Shaofeng Cai, Jie Chen +3
Online anomaly detection (OAD) plays a pivotal role in real-time analytics and decision-making for evolving data streams. However, existing methods often rely on costly retraining…
LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation
Yuqian Yuan, Wenqiao Zhang, Juekai Lin +7
Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks requiring precise object-level…
Towards Effective Orchestration of AI x DB Workloads
Naili Xing, Haotian Gao, Zhanhao Zhao +6
AI-driven analytics are increasingly crucial to data-centric decision-making. Executing relational and AI operators in separate runtimes prevents the database optimizer and runtime…
CtrlCoT: Dual-Granularity Chain-of-Thought Compression for Controllable Reasoning
Zhenxuan Fan, Jie Cao, Yang Dai +5
Chain-of-thought (CoT) prompting improves LLM reasoning but incurs high latency and memory cost due to verbose traces, motivating CoT compression with preserved correctness. Existi…
CLEAR-Mamba:Towards Accurate, Adaptive and Trustworthy Multi-Sequence Ophthalmic Angiography Classification
Zhuonan Wang, Wenjie Yan, Wenqiao Zhang +5
Medical image classification is a core task in computer-aided diagnosis (CAD), playing a pivotal role in early disease detection, treatment planning, and patient prognosis assessme…
NeurIDA: Dynamic Modeling for Effective In-Database Analytics
Lingze Zeng, Naili Xing, Shaofeng Cai +4
Relational Database Management Systems (RDBMS) manage complex, interrelated data and support a broad spectrum of analytical tasks. With the growing demand for predictive analytics,…
Generative AI for Healthcare: Fundamentals, Challenges, and Perspectives
Gang Chen, Changshuo Liu, Gene Anne Ooi +7
Generative Artificial Intelligence (GenAI) is taking the world by storm. It promises transformative opportunities for advancing and disrupting existing practices, including healthc…
NeurStore: Efficient In-database Deep Learning Model Management System
Siqi Xiang, Sheng Wang, Xiaokui Xiao +3
With the prevalence of in-database AI-powered analytics, there is an increasing demand for database systems to efficiently manage the ever-expanding number and size of deep learnin…
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Yanyan Shen +3
Machine learning has demonstrated transformative potential for database operations, such as query optimization and in-database data analytics. However, dynamic database environment…
HAKES: Scalable Vector Database for Embedding Search Service
Guoyu Hu, Shaofeng Cai, Tien Tuan Anh Dinh +4
Modern deep learning models capture the semantics of complex data by transforming them into high-dimensional embedding vectors. Emerging applications, such as retrieval-augmented g…
EyecareGPT: Boosting Comprehensive Ophthalmology Understanding with Tailored Dataset, Benchmark and Model
Sijing Li, Tianwei Lin, Lingshuai Lin +9
Medical Large Vision-Language Models (Med-LVLMs) demonstrate significant potential in healthcare, but their reliance on general medical data and coarse-grained global visual unders…
NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling
Zhanhao Zhao, Haotian Gao, Naili Xing +5
Learned database components, which deeply integrate machine learning into their design, have been extensively studied in recent years. Given the dynamism of databases, where data a…
Modeling Concurrency Control as a Learnable Function
Hexiang Pan, Shaofeng Cai, Tien Tuan Anh Dinh +4
Concurrency control (CC) algorithms are important in modern transactional databases, as they enable high performance by executing transactions concurrently while ensuring correctne…
HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation
Tianwei Lin, Wenqiao Zhang, Sijing Li +12
We present HealthGPT, a powerful Medical Large Vision-Language Model (Med-LVLM) that integrates medical visual comprehension and generation capabilities within a unified autoregres…
SeSeMI: Secure Serverless Model Inference on Sensitive Data
Guoyu Hu, Yuncheng Wu, Gang Chen +2
Model inference systems are essential for implementing end-to-end data analytics pipelines that deliver the benefits of machine learning models to users. Existing cloud-based model…
NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
Zhanhao Zhao, Shaofeng Cai, Haotian Gao +8
Databases are increasingly embracing AI to provide autonomous system optimization and intelligent in-database analytics, aiming to relieve end-user burdens across various industry…
VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection
Fei Xiao, Shaofeng Cai, Gang Chen +3
Fraud detection presents a challenging task characterized by ever-evolving fraud patterns and scarce labeled data. Existing methods predominantly rely on graph-based or sequence-ba…
NeurDB: An AI-powered Autonomous Data System
Beng Chin Ooi, Shaofeng Cai, Gang Chen +9
In the wake of rapid advancements in artificial intelligence (AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB (AIxDB) promises…
Powering In-Database Dynamic Model Slicing for Structured Data Analytics
Lingze Zeng, Naili Xing, Shaofeng Cai +4
Relational database management systems (RDBMS) are widely used for the storage of structured data. To derive insights beyond statistical aggregation, we typically have to extract s…
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection
Jiaqi Zhu, Shaofeng Cai, Fang Deng +2
Large vision-language models (LVLMs) are markedly proficient in deriving visual representations guided by natural language. Recent explorations have utilized LVLMs to tackle zero-s…