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20232026
most citedMETER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection

23 citations · 63 across the 23 of their papers we have counts for

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9 papers · 1 filter

cs.AI2026

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…

cs.MA2026

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…

cs.LG2026

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…

cs.DB2026

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…

cs.LG2026

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…

cs.CV2026

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…

cs.DB2026

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…

cs.AI2026

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…

cs.CV2026

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…