6 citations · 31 across the 14 of their papers we have counts for
16 papers
AUGUstus: Autonomous Driving VLA Model with Unified Generation and Understanding
Yuqi Ye, Caigao Jiang, Zhuonan Wang +12
Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in long-tail scenarios. However…
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Qize Yu, Lianrui Fan, Boyu Chen +23
Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fast enough for closed-loop cont…
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
Gangwei Jiang, Caigao Jiang, Zhaoyi Li +5
Catastrophic forgetting (CF) poses a significant challenge in machine learning, where a model forgets previously learned information upon learning new tasks. Despite the advanced c…
ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning
Yi Huang, Fangyin Cheng, Fan Zhou +7
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in data analytics when integrated with Multi-Agent Systems (MAS). However, these systems oft…
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch
Caigao Jiang, Xiang Shu, Hong Qian +4
Optimization problems are prevalent across various scenarios. Formulating and then solving optimization problems described by natural language often requires highly specialized hum…
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…
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference
Yan Wang, Zhixuan Chu, Tao Zhou +9
Asynchronous time series, also known as temporal event sequences, are the basis of many applications throughout different industries. Temporal point processes(TPPs) are the standar…
Continual Learning in Predictive Autoscaling
Hongyan Hao, Zhixuan Chu, Shiyi Zhu +7
Predictive Autoscaling is used to forecast the workloads of servers and prepare the resources in advance to ensure service level objectives (SLOs) in dynamic cloud environments. Ho…
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine
Siqiao Xue, Fan Zhou, Yi Xu +10
We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain. Our system harnesses a large language model of GPT architecture that has been tu…
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Siqiao Xue, Xiaoming Shi, Zhixuan Chu +9
Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point…
Learning Large-scale Universal User Representation with Sparse Mixture of Experts
Caigao Jiang, Siqiao Xue, James Zhang +3
Learning user sequence behaviour embedding is very sophisticated and challenging due to the complicated feature interactions over time and high dimensions of user features. Recent…
Unit Ball Model for Embedding Hierarchical Structures in the Complex Hyperbolic Space
Huiru Xiao, Caigao Jiang, Yangqiu Song +2
Learning the representation of data with hierarchical structures in the hyperbolic space attracts increasing attention in recent years. Due to the constant negative curvature, the…