Natural Language Understanding

TimeCMA: Towards LLM-Empowered Time Series Forecasting via Cross-Modality Alignment

The widespread adoption of scalable mobile sensing has led to large amounts of time series data for real-world applications. A fundamental application is multivariate time series forecasting (MTSF), which aims to predict future time series values …

A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Mode

Time series data are ubiquitous across various domains, making time series analysis critically important. Traditional time series models are task-specific, featuring singular functionality and limited generalization capacity. Recently, large language …

PET-SQL: A Prompt-enhanced Two-stage Text-to-SQL Framework with Cross-consistency

We are ranked as the top-1 solution wolrd wide in the [Text-to-SQL leaderboard](https://paperswithcode.com/sota/text-to-sql-on-spider)

SQLBench: Benchmarking the Text-to-SQL Capability of Large Language Models - A Comprehensive Evaluation

Large Language Models (LLMs) have emerged as a powerful tool in advancing the Text-to-SQL task, significantly outperforming traditional methods. Nevertheless, as a nascent research field, there is still no consensus on the optimal prompt templates …