activity
20232026
most citedUAV Trajectory Tracking via RNN-enhanced IMM-KF with ADS-B Data

1 citations · 4 across the 10 of their papers we have counts for

collaborators

10 papers

cs.DB2026

DIVER: A Robust Text-to-SQL System with Dynamic Interactive Value Linking and Evidence Reasoning

Yafeng Nan, Haifeng Sun, Zirui Zhuang +5

In the era of large language models, Text-to-SQL, as a natural language interface for databases, is playing an increasingly important role. The sota Text-to-SQL models have achieve…

cs.LG2025

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting

Chengsen Wang, Qi Qi, Jingyu Wang +3

Time series forecasting holds significant importance across various industries, including finance, transportation, energy, healthcare, and climate. Despite the widespread use of li…

cs.LG2025★ 1 cited

MergeQuant: Accurate 4-bit Static Quantization of Large Language Models by Channel-wise Calibration

Jinguang Wang, Jingyu Wang, Haifeng Sun +6

Quantization has been widely used to compress and accelerate inference of large language models (LLMs). Existing methods focus on exploring the per-token dynamic calibration to ens…

cs.LG2025

OIPR: Evaluation for Time-series Anomaly Detection Inspired by Operator Interest

Yuhan Jing, Jingyu Wang, Lei Zhang +6

With the growing adoption of time-series anomaly detection (TAD) technology, numerous studies have employed deep learning-based detectors to analyze time-series data in the fields…

cs.CL2024

ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data

Chengsen Wang, Qi Qi, Jingyu Wang +5

Human experts typically integrate numerical and textual multimodal information to analyze time series. However, most traditional deep learning predictors rely solely on unimodal nu…

cs.LG2024★ 1 cited

Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly Detection

Yuanyi Wang, Haifeng Sun, Chengsen Wang +6

Anomaly detection in multivariate time series (MTS) is crucial for various applications in data mining and industry. Current industrial methods typically approach anomaly detection…