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…

cs.LG2024★ 1 cited

Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective

Chengsen Wang, Qi Qi, Jingyu Wang +4

Time series forecasting has played a pivotal role across various industries, including finance, transportation, energy, healthcare, and climate. Due to the abundant seasonal inform…

cs.CL2024

OutlierTune: Efficient Channel-Wise Quantization for Large Language Models

Jinguang Wang, Yuexi Yin, Haifeng Sun +5

Quantizing the activations of large language models (LLMs) has been a significant challenge due to the presence of structured outliers. Most existing methods focus on the per-token…

cs.IR2024

Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation

Yuanyi Wang, Wei Tang, Haifeng Sun +5

Weakly Supervised Entity Alignment (EA) is the task of identifying equivalent entities across diverse knowledge graphs (KGs) using only a limited number of seed alignments. Despite…

eess.SY2023★ 1 cited

UAV Trajectory Tracking via RNN-enhanced IMM-KF with ADS-B Data

Yian Zhu, Ziye Jia, Qihui Wu +4

With the increasing use of autonomous unmanned aerial vehicles (UAVs), it is critical to ensure that they are continuously tracked and controlled, especially when UAVs operate beyo…