57 citations · 175 across the 17 of their papers we have counts for
17 papers
HyperLISTA-ABT: An Ultra-light Unfolded Network for Accurate Multi-component Differential Tomographic SAR Inversion
Kun Qian, Yuanyuan Wang, Peter Jung +2
Deep neural networks based on unrolled iterative algorithms have achieved remarkable success in sparse reconstruction applications, such as synthetic aperture radar (SAR) tomograph…
Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System
Jianguo Zhang, Stephen Roller, Kun Qian +6
End-to-end task-oriented dialogue (TOD) systems have achieved promising performance by leveraging sophisticated natural language understanding and natural language generation capab…
DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI
Jianguo Zhang, Kun Qian, Zhiwei Liu +7
Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversi…
Basis Pursuit Denoising via Recurrent Neural Network Applied to Super-resolving SAR Tomography
Kun Qian, Yuanyuan Wang, Peter Jung +2
Finding sparse solutions of underdetermined linear systems commonly requires the solving of L1 regularized least squares minimization problem, which is also known as the basis purs…
Elucidating the Role of Prelithiation in Si-based Anodes for Interface Stabilization
Shuang Bai, Wurigumula Bao, Kun Qian +7
Prelithiation as a facile and effective method to compensate the lithium inventory loss in the initial cycle has progressed considerably both on anode and cathode sides. However, m…
User Adaptive Language Learning Chatbots with a Curriculum
Kun Qian, Ryan Shea, Yu Li +2
Along with the development of systems for natural language understanding and generation, dialog systems have been widely adopted for language learning and practicing. Many current…
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking
Derek Chen, Kun Qian, Zhou Yu
Prompt-based methods with large pre-trained language models (PLMs) have shown impressive unaided performance across many NLP tasks. These models improve even further with the addit…
A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era
Zhao Ren, Yi Chang, Thanh Tam Nguyen +3
Heart sound auscultation has been applied in clinical usage for early screening of cardiovascular diseases. Due to the high demand for auscultation expertise, automatic auscultatio…
KRLS: Improving End-to-End Response Generation in Task Oriented Dialog with Reinforced Keywords Learning
Xiao Yu, Qingyang Wu, Kun Qian +1
In task-oriented dialogs (TOD), reinforcement learning (RL) algorithms train a model to directly optimize response for task-related metrics. However, RL needs to perform exploratio…
Knowledge Transfer For On-Device Speech Emotion Recognition with Neural Structured Learning
Yi Chang, Zhao Ren, Thanh Tam Nguyen +2
Speech emotion recognition (SER) has been a popular research topic in human-computer interaction (HCI). As edge devices are rapidly springing up, applying SER to edge devices is pr…
Cryogenic in-memory computing using magnetic topological insulators
Yuting Liu, Albert Lee, Kun Qian +17
Machine learning algorithms have been proven effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementati…
Learning a Better Initialization for Soft Prompts via Meta-Learning
Yukun Huang, Kun Qian, Zhou Yu
Prompt tuning (PT) is an effective approach to adapting pre-trained language models to downstream tasks. Without a good initialization, prompt tuning doesn't perform well under few…
Audio Self-supervised Learning: A Survey
Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro +5
Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data wi…
-Net: Superresolving SAR Tomographic Inversion via Deep Learning
Kun Qian, Yuanyuan Wang, Yilei Shi +1
Synthetic aperture radar tomography (TomoSAR) has been extensively employed in 3-D reconstruction in dense urban areas using high-resolution SAR acquisitions. Compressive sensing (…
Memformer: A Memory-Augmented Transformer for Sequence Modeling
Qingyang Wu, Zhenzhong Lan, Kun Qian +3
Transformers have reached remarkable success in sequence modeling. However, these models have efficiency issues as they need to store all the history token-level representations as…
Low-resource Deep Entity Resolution with Transfer and Active Learning
Jungo Kasai, Kun Qian, Sairam Gurajada +2
Entity resolution (ER) is the task of identifying different representations of the same real-world entities across databases. It is a key step for knowledge base creation and text…
Domain Adaptive Dialog Generation via Meta Learning
Kun Qian, Zhou Yu
Domain adaptation is an essential task in dialog system building because there are so many new dialog tasks created for different needs every day. Collecting and annotating trainin…