11 citations · 27 across the 11 of their papers we have counts for
11 papers
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting
Fan Zhou, Chen Pan, Lintao Ma +9
Time series forecasts of different temporal granularity are widely used in real-world applications, e.g., sales prediction in days and weeks for making different inventory plans. H…
DB-GPT-Hub: Towards Open Benchmarking Text-to-SQL Empowered by Large Language Models
Fan Zhou, Siqiao Xue, Danrui Qi +8
Large language models (LLMs) becomes the dominant paradigm for the challenging task of text-to-SQL. LLM-empowered text-to-SQL methods are typically categorized into prompting-based…
Demonstration of DB-GPT: Next Generation Data Interaction System Empowered by Large Language Models
Siqiao Xue, Danrui Qi, Caigao Jiang +13
The recent breakthroughs in large language models (LLMs) are positioned to transition many areas of software. The technologies of interacting with data particularly have an importa…
DB-GPT: Empowering Database Interactions with Private Large Language Models
Siqiao Xue, Caigao Jiang, Wenhui Shi +13
The recent breakthroughs in large language models (LLMs) are positioned to transition many areas of software. Database technologies particularly have an important entanglement with…
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt
Gangwei Jiang, Caigao Jiang, Siqiao Xue +4
Continual pre-training has been urgent for adapting a pre-trained model to a multitude of domains and tasks in the fast-evolving world. In practice, a continually pre-trained model…
Prompt-augmented Temporal Point Process for Streaming Event Sequence
Siqiao Xue, Yan Wang, Zhixuan Chu +7
Neural Temporal Point Processes (TPPs) are the prevalent paradigm for modeling continuous-time event sequences, such as user activities on the web and financial transactions. In re…