15 papers
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…
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…
Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models
Huazheng Wang, Yongcheng Jing, Haifeng Sun +4
In this paper, we investigate knowledge forgetting in large language models with a focus on its generalisation, ensuring that models forget not only specific training samples but a…
ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Data
Chengsen Wang, Qi Qi, Zhongwen Rao +3
Conventional forecasting methods rely on unimodal time series data, limiting their ability to exploit rich textual information. Recently, large language models (LLMs) and time seri…
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…
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…