Search Results for author: Kun Qian

Found 47 papers, 11 papers with code

Enhancing Item-level Bundle Representation for Bundle Recommendation

1 code implementation28 Nov 2023 Xiaoyu Du, Kun Qian, Yunshan Ma, Xinguang Xiang

In this paper, we propose a novel approach EBRec, short of Enhanced Bundle Recommendation, which incorporates two enhanced modules to explore inherent item-level bundle representations.

Contrastive Learning

FLEEK: Factual Error Detection and Correction with Evidence Retrieved from External Knowledge

no code implementations26 Oct 2023 Farima Fatahi Bayat, Kun Qian, Benjamin Han, Yisi Sang, Anton Belyi, Samira Khorshidi, Fei Wu, Ihab F. Ilyas, Yunyao Li

Detecting factual errors in textual information, whether generated by large language models (LLM) or curated by humans, is crucial for making informed decisions.

ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding

no code implementations7 Oct 2023 Zixuan Liu, Gaurush Hiranandani, Kun Qian, Eddie W. Huang, Yi Xu, Belinda Zeng, Karthik Subbian, Sheng Wang

ForeSeer transfers reviews from similar products on a large product graph and exploits these reviews to predict aspects that might emerge in future reviews.

Graph Embedding Link Prediction

HyperLISTA-ABT: An Ultra-light Unfolded Network for Accurate Multi-component Differential Tomographic SAR Inversion

no code implementations28 Sep 2023 Kun Qian, Yuanyuan Wang, Peter Jung, Yilei Shi, Xiao Xiang Zhu

Deep neural networks based on unrolled iterative algorithms have achieved remarkable success in sparse reconstruction applications, such as synthetic aperture radar (SAR) tomographic inversion (TomoSAR).

3D Reconstruction

Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System

no code implementations16 Aug 2023 JianGuo Zhang, Stephen Roller, Kun Qian, Zhiwei Liu, Rui Meng, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong

End-to-end task-oriented dialogue (TOD) systems have achieved promising performance by leveraging sophisticated natural language understanding and natural language generation capabilities of pre-trained models.

Natural Language Understanding Retrieval +1

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI

1 code implementation19 Jul 2023 JianGuo Zhang, Kun Qian, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Huan Wang, Silvio Savarese, Caiming Xiong

Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversity and comprehensiveness.

Few-Shot Learning Language Modelling +1

Basis Pursuit Denoising via Recurrent Neural Network Applied to Super-resolving SAR Tomography

no code implementations23 May 2023 Kun Qian, Yuanyuan Wang, Peter Jung, Yilei Shi, Xiao Xiang Zhu

An emerging technique known as deep unrolling provided a good combination of the descriptive ability of neural networks, explainable, and computational efficiency for BPDN.

Denoising Descriptive +2

Learning to Seek: Multi-Agent Online Source Seeking Against Non-Stochastic Disturbances

no code implementations29 Apr 2023 Bin Du, Kun Qian, Christian Claudel, Dengfeng Sun

This paper proposes to leverage the emerging~learning techniques and devise a multi-agent online source {seeking} algorithm under unknown environment.

User Adaptive Language Learning Chatbots with a Curriculum

no code implementations11 Apr 2023 Kun Qian, Ryan Shea, Yu Li, Luke Kutszik Fryer, Zhou Yu

Along with the development of systems for natural language understanding and generation, dialog systems have been widely adopted for language learning and practicing.

Natural Language Understanding

Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking

no code implementations12 Feb 2023 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.

Dialogue State Tracking Meta-Learning +1

A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era

no code implementations23 Jan 2023 Zhao Ren, Yi Chang, Thanh Tam Nguyen, Yang Tan, Kun Qian, Björn W. Schuller

Deep learning has been successfully applied to heart sound analysis in the past years.

KRLS: Improving End-to-End Response Generation in Task Oriented Dialog with Reinforced Keywords Learning

1 code implementation30 Nov 2022 Xiao Yu, Qingyang Wu, Kun Qian, Zhou Yu

In task-oriented dialogs (TOD), reinforcement learning (RL) algorithms train a model to directly optimize response for task-related metrics.

Language Modelling reinforcement-learning +2

Boosting Personalised Musculoskeletal Modelling with Physics-informed Knowledge Transfer

no code implementations22 Nov 2022 Jie Zhang, Yihui Zhao, Tianzhe Bao, Zhenhong Li, Kun Qian, Alejandro F. Frangi, Sheng Quan Xie, Zhi-Qiang Zhang

The salient advantages of the proposed framework are twofold: 1) For the generic model, physics-based domain knowledge is embedded into the loss function of the data-driven model as soft constraints to penalise/regularise the data-driven model.

Transfer Learning

Knowledge Transfer For On-Device Speech Emotion Recognition with Neural Structured Learning

1 code implementation26 Oct 2022 Yi Chang, Zhao Ren, Thanh Tam Nguyen, Kun Qian, Björn W. Schuller

Our experiments demonstrate that training a lightweight SER model on the target dataset with speech samples and graphs can not only produce small SER models, but also enhance the model performance compared to models with speech samples only and those using classic transfer learning strategies.

Speech Emotion Recognition Transfer Learning

Learning a Better Initialization for Soft Prompts via Meta-Learning

no code implementations25 May 2022 Yukun Huang, Kun Qian, Zhou Yu

So pre-trained prompt tuning (PPT) is proposed to initialize prompts by leveraging pre-training data.


Quantum Deep Learning for Mutant COVID-19 Strain Prediction

no code implementations4 Mar 2022 Yu-Xin Jin, Jun-Jie Hu, Qi Li, Zhi-Cheng Luo, Fang-Yan Zhang, Hao Tang, Kun Qian, Xian-Min Jin

New COVID-19 epidemic strains like Delta and Omicron with increased transmissibility and pathogenicity emerge and spread across the whole world rapidly while causing high mortality during the pandemic period.

Audio Self-supervised Learning: A Survey

no code implementations2 Mar 2022 Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro, Kun Qian, Xin Jing, Alexander Kathan, Bin Hu, Bjoern W. Schuller

Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data without requiring human annotations, which is an expensive and time consuming task.

Self-Supervised Learning

AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All

no code implementations15 Dec 2021 Lei Zuo, Kun Qian, Bowen Yang, Zhou Yu

A commonly observed problem of the state-of-the-art natural language technologies, such as Amazon Alexa and Apple Siri, is that their services do not extend to most developing countries' citizens due to language barriers.


Database Search Results Disambiguation for Task-Oriented Dialog Systems

no code implementations NAACL 2022 Kun Qian, Ahmad Beirami, Satwik Kottur, Shahin Shayandeh, Paul Crook, Alborz Geramifard, Zhou Yu, Chinnadhurai Sankar

We find that training on our augmented dialog data improves the model's ability to deal with ambiguous scenarios, without sacrificing performance on unmodified turns.

Multi-Task Learning

$\boldsymbolγ$-Net: Superresolving SAR Tomographic Inversion via Deep Learning

no code implementations8 Dec 2021 Kun Qian, Yuanyuan Wang, Yilei Shi, Xiao Xiang Zhu

This superior performance comes at the cost of extra computational burdens, because of the sparse reconstruction, which cannot be solved analytically and we need to employ computationally expensive iterative solvers.

Compressive Sensing Super-Resolution

MS$^2$-Transformer: An End-to-End Model for MS/MS-assisted Molecule Identification

no code implementations29 Sep 2021 Mengji Zhang, Yingce Xia, Nian Wu, Kun Qian, Jianyang Zeng

Manually interpreting the MS/MS spectrum into the molecules (i. e., the simplified molecular-input line-entry system, SMILES) is often costly and cumbersome, mainly due to the synthesis and labeling of isotopes and the requirement of expert knowledge.

Robust Multimodal Vehicle Detection in Foggy Weather Using Complementary Lidar and Radar Signals

1 code implementation CVPR 2021 Kun Qian, Shilin Zhu, Xinyu Zhang, Li Erran Li

Vehicle detection with visual sensors like lidar and camera is one of the critical functions enabling autonomous driving.

Autonomous Driving

Annotation Inconsistency and Entity Bias in MultiWOZ

no code implementations SIGDIAL (ACL) 2021 Kun Qian, Ahmad Beirami, Zhouhan Lin, Ankita De, Alborz Geramifard, Zhou Yu, Chinnadhurai Sankar

In this work, we identify an overlooked issue with dialog state annotation inconsistencies in the dataset, where a slot type is tagged inconsistently across similar dialogs leading to confusion for DST modeling.

dialog state tracking Memorization +2

A Student-Teacher Architecture for Dialog Domain Adaptation under the Meta-Learning Setting

no code implementations6 Apr 2021 Kun Qian, Wei Wei, Zhou Yu

The most recent researches on domain adaption focus on giving the model a better initialization, rather than optimizing the adaptation process.

Domain Adaptation Meta-Learning

Recent Advances in Computer Audition for Diagnosing COVID-19: An Overview

no code implementations8 Dec 2020 Kun Qian, Bjorn W. Schuller, Yoshiharu Yamamoto

Computer audition (CA) has been demonstrated to be efficient in healthcare domains for speech-affecting disorders (e. g., autism spectrum, depression, or Parkinson's disease) and body sound-affecting abnormalities (e. g., abnormal bowel sounds, heart murmurs, or snore sounds).

Towards SAR Tomographic Inversion via Sparse Bayesian Learning

no code implementations24 Nov 2020 Kun Qian, Yuanyuan Wang, Xiaoxiang Zhu

Existing SAR tomography (TomoSAR) algorithms are mostly based on an inversion of the SAR imaging model, which are often computationally expensive.

Learning Structured Representations of Entity Names using Active Learning and Weak Supervision

1 code implementation EMNLP 2020 Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation.

Active Learning

MeDaS: An open-source platform as service to help break the walls between medicine and informatics

no code implementations12 Jul 2020 Liang Zhang, Johann Li, Ping Li, Xiaoyuan Lu, Peiyi Shen, Guangming Zhu, Syed Afaq Shah, Mohammed Bennarmoun, Kun Qian, Björn W. Schuller

To the best of our knowledge, MeDaS is the first open-source platform proving a collaborative and interactive service for researchers from a medical background easily using DL related toolkits, and at the same time for scientists or engineers from information sciences to understand the medical knowledge side.

Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases

no code implementations WS 2020 Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish

Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.

Question Answering

deepSELF: An Open Source Deep Self End-to-End Learning Framework

no code implementations11 May 2020 Tomoya Koike, Kun Qian, Björn W. Schuller, Yoshiharu Yamamoto

To the best of our knowledge, it is the first public toolkit assembling a series of state-of-the-art deep learning technologies.

Image Generation

An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety

no code implementations30 Apr 2020 Jing Han, Kun Qian, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu, Huaiyuan Zheng, Wei Ji, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, Björn W. Schuller

In particular, by analysing speech recordings from these patients, we construct audio-only-based models to automatically categorise the health state of patients from four aspects, including the severity of illness, sleep quality, fatigue, and anxiety.

Sleep Quality

COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis

no code implementations24 Mar 2020 Björn W. Schuller, Dagmar M. Schuller, Kun Qian, Juan Liu, Huaiyuan Zheng, Xiao Li

We come to the conclusion that CA appears ready for implementation of (pre-)diagnosis and monitoring tools, and more generally provides rich and significant, yet so far untapped potential in the fight against COVID-19 spread.

End-to-End Trainable Non-Collaborative Dialog System

1 code implementation25 Nov 2019 Yu Li, Kun Qian, Weiyan Shi, Zhou Yu

End-to-end task-oriented dialog models have achieved promising performance on collaborative tasks where users willingly coordinate with the system to complete a given task.


How to Build User Simulators to Train RL-based Dialog Systems

1 code implementation IJCNLP 2019 Weiyan Shi, Kun Qian, Xuewei Wang, Zhou Yu

We propose a method of standardizing user simulator building that can be used by the community to compare dialog system quality using the same set of user simulators fairly.

Reinforcement Learning (RL) User Simulation

Adabot: Fault-Tolerant Java Decompiler

no code implementations14 Aug 2019 Zhiming Li, Qing Wu, Kun Qian

Specifically, in terms of BLEU-4 and Word Error Rate (WER), our performance has reached 94. 50% and 2. 65% on the redundant test set; 92. 30% and 3. 48% on the purified test set.

Machine Translation NMT +2

Low-resource Deep Entity Resolution with Transfer and Active Learning

no code implementations ACL 2019 Jungo Kasai, Kun Qian, Sairam Gurajada, Yunyao Li, Lucian Popa

Recent adaptation of deep learning methods for ER mitigates the need for dataset-specific feature engineering by constructing distributed representations of entity records.

Active Learning Entity Resolution +2

Domain Adaptive Dialog Generation via Meta Learning

1 code implementation ACL 2019 Kun Qian, Zhou Yu

We train a dialog system model using multiple rich-resource single-domain dialog data by applying the model-agnostic meta-learning algorithm to dialog domain.

Domain Adaptation Meta-Learning

Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data

no code implementations29 Mar 2019 Zixing Zhang, Jing Han, Kun Qian, Christoph Janott, Yanan Guo, Bjoern Schuller

One of the frontier issues that severely hamper the development of automatic snore sound classification (ASSC) associates to the lack of sufficient supervised training data.

Classification Data Augmentation +2

Knowledge Refinement via Rule Selection

no code implementations29 Jan 2019 Phokion G. Kolaitis, Lucian Popa, Kun Qian

In this paper, we carry out a systematic complexity-theoretic investigation of the following rule selection problem: given a set of rules specified by Horn formulas, and a pair of an input database and an output database, find a subset of the rules that minimizes the total error, that is, the number of false positive and false negative errors arising from the selected rules.

Entity Resolution

Learning audio sequence representations for acoustic event classification

no code implementations27 Jul 2017 Zixing Zhang, Ding Liu, Jing Han, Kun Qian, Björn Schuller

Extensive evaluation on a large-size acoustic event database is performed, and the empirical results demonstrate that the learnt audio sequence representation yields a significant performance improvement by a large margin compared with other state-of-the-art hand-crafted sequence features for AEC.

Classification General Classification

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