17 citations · 24 across the 10 of their papers we have counts for
10 papers
Rethinking Dense Retrieval's Few-Shot Ability
Si Sun, Yida Lu, Shi Yu +6
Few-shot dense retrieval (DR) aims to effectively generalize to novel search scenarios by learning a few samples. Despite its importance, there is little study on specialized datas…
Distributed Data-driven Predictive Control via Dissipative Behavior Synthesis
Yitao Yan, Jie Bao, Biao Huang
This paper presents a distributed data-driven predictive control (DDPC) approach using the behavioral framework. It aims to design a network of controllers for an interconnected sy…
Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives
Si Sun, Chenyan Xiong, Yue Yu +3
In this paper, we investigate the instability in the standard dense retrieval training, which iterates between model training and hard negative selection using the being-trained mo…
A Contraction-constrained Model Predictive Control for Nonlinear Processes using Disturbance Forecasts
Ryan McCloy, Lai Wei, Jie Bao
Model predictive control (MPC) has become the most widely used advanced control method in process industry. In many cases, forecasts of the disturbances are available, e.g., predic…
A Contraction-constrained Model Predictive Control for Multi-timescale Nonlinear Processes
Ryan McCloy, Lai Wei, Jie Bao
Many chemical processes exhibit diverse timescale dynamics with a strong coupling between timescale sensitive variables. Model predictive control with a non-uniformly spaced optimi…
Adaptive Contraction-based Control of Uncertain Nonlinear Processes using Neural Networks
Lai Wei, Ryan McCloy, Jie Bao
Driven by the flexible manufacturing trend in the process control industry and the uncertain nature of chemical process models, this article aims to achieve offset-free tracking fo…
Electrolyte Flow Rate Control for Vanadium Redox Flow Batteries using the Linear Parameter Varying Framework
Ryan McCloy, Yifeng Li, Jie Bao +1
In this article, an electrolyte flow rate control approach is developed for an all-vanadium redox flow battery (VRB) system based on the linear parameter varying (LPV) framework. T…
Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
Lai Wei, Ryan McCloy, Jie Bao
In response to the continuously changing feedstock supply and market demand for products with different specifications, the processes need to be operated at time-varying operating…
Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision
Si Sun, Yingzhuo Qian, Zhenghao Liu +5
The effectiveness of Neural Information Retrieval (Neu-IR) often depends on a large scale of in-domain relevance training signals, which are not always available in real-world rank…
Capturing Global Informativeness in Open Domain Keyphrase Extraction
Si Sun, Zhenghao Liu, Chenyan Xiong +2
Open-domain KeyPhrase Extraction (KPE) aims to extract keyphrases from documents without domain or quality restrictions, e.g., web pages with variant domains and qualities. Recentl…