Search Results for author: Qi Liu

Found 217 papers, 86 papers with code

Efficient and accurate neural field reconstruction using resistive memory

no code implementations15 Apr 2024 Yifei Yu, Shaocong Wang, Woyu Zhang, Xinyuan Zhang, Xiuzhe Wu, Yangu He, Jichang Yang, Yue Zhang, Ning Lin, Bo wang, Xi Chen, Songqi Wang, Xumeng Zhang, Xiaojuan Qi, Zhongrui Wang, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

The GE harnesses the intrinsic stochasticity of resistive memory for efficient input encoding, while the PE achieves precise weight mapping through a Hardware-Aware Quantization (HAQ) circuit.

Event Grounded Criminal Court View Generation with Cooperative (Large) Language Models

2 code implementations10 Apr 2024 Linan Yue, Qi Liu, Lili Zhao, Li Wang, Weibo Gao, Yanqing An

Then, we incorporate the extracted events into court view generation by merging case facts and events.

Event Extraction

Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model

no code implementations8 Apr 2024 Jichang Yang, Hegan Chen, Jia Chen, Songqi Wang, Shaocong Wang, Yifei Yu, Xi Chen, Bo wang, Xinyuan Zhang, Binbin Cui, Ning Lin, Meng Xu, Yi Li, Xiaoxin Xu, Xiaojuan Qi, Zhongrui Wang, Xumeng Zhang, Dashan Shang, Han Wang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Demonstrating equivalent generative quality to the software baseline, our system achieved remarkable enhancements in generative speed for both unconditional and conditional generation tasks, by factors of 64. 8 and 156. 5, respectively.


Survey of Computerized Adaptive Testing: A Machine Learning Perspective

1 code implementation31 Mar 2024 Qi Liu, Yan Zhuang, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen

Computerized Adaptive Testing (CAT) provides an efficient and tailored method for assessing the proficiency of examinees, by dynamically adjusting test questions based on their performance.

cognitive diagnosis Question Selection +1

Unleashing the Potential of Large Language Models for Predictive Tabular Tasks in Data Science

no code implementations29 Mar 2024 Yazheng Yang, Yuqi Wang, Sankalok Sen, Lei LI, Qi Liu

Despite their proficiency in comprehending natural language, LLMs fall short in dealing with structured tabular data.

Imputation In-Context Learning

An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models

no code implementations20 Mar 2024 Qi Liu, Gang Guo, Jiaxin Mao, Zhicheng Dou, Ji-Rong Wen, Hao Jiang, Xinyu Zhang, Zhao Cao

Based on these findings, we then propose several simple document pruning methods to reduce the storage overhead and compare the effectiveness of different pruning methods on different late-interaction models.


Learning Transferable Time Series Classifier with Cross-Domain Pre-training from Language Model

no code implementations19 Mar 2024 Mingyue Cheng, Xiaoyu Tao, Qi Liu, Hao Zhang, Yiheng Chen, Chenyi Lei

To address this challenge, we propose CrossTimeNet, a novel cross-domain SSL learning framework to learn transferable knowledge from various domains to largely benefit the target downstream task.

Language Modelling Time Series +1

Advancing Time Series Classification with Multimodal Language Modeling

no code implementations19 Mar 2024 Mingyue Cheng, Yiheng Chen, Qi Liu, Zhiding Liu, Yucong Luo

In this work, we propose InstructTime, a novel attempt to reshape time series classification as a learning-to-generate paradigm.

Classification Language Modelling +2

Clinically Feasible Diffusion Reconstruction for Highly-Accelerated Cardiac Cine MRI

no code implementations13 Mar 2024 Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao, Jian Xu, Qi Liu, Terrence Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun

The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processing time poses a challenge.

Spatiotemporal Diffusion Model with Paired Sampling for Accelerated Cardiac Cine MRI

no code implementations13 Mar 2024 Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao, Jian Xu, Qi Liu, Terrence Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun

Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring.

Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform

no code implementations13 Mar 2024 Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen

Through this gateway, users have the opportunity to submit their questions, testing the models on a personalized and potentially broader range of capabilities.

Language Modelling Large Language Model

Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery

1 code implementation12 Mar 2024 Linan Yue, Qi Liu, Yichao Du, Li Wang, Weibo Gao, Yanqing An

Since existing methods still suffer from adopting the shortcuts in data to compose rationales and limited large-scale annotated rationales by human, in this paper, we propose a Shortcuts-fused Selective Rationalization (SSR) method, which boosts the rationalization by discovering and exploiting potential shortcuts.

Cooperative Classification and Rationalization for Graph Generalization

1 code implementation10 Mar 2024 Linan Yue, Qi Liu, Ye Liu, Weibo Gao, Fangzhou Yao, Wenfeng Li

To address these challenges, in this paper, we propose a Cooperative Classification and Rationalization (C2R) method, consisting of the classification and the rationalization module.

Graph Classification Knowledge Distillation

A Dataset for the Validation of Truth Inference Algorithms Suitable for Online Deployment

1 code implementation10 Mar 2024 Fei Wang, Haoyu Liu, Haoyang Bi, Xiangzhuang Shen, Renyu Zhu, Runze Wu, Minmin Lin, Tangjie Lv, Changjie Fan, Qi Liu, Zhenya Huang, Enhong Chen

In this paper, we introduce a substantial crowdsourcing annotation dataset collected from a real-world crowdsourcing platform.

Unified Uncertainty Estimation for Cognitive Diagnosis Models

no code implementations9 Mar 2024 Fei Wang, Qi Liu, Enhong Chen, Chuanren Liu, Zhenya Huang, Jinze Wu, Shijin Wang

Specifically, based on the idea of estimating the posterior distributions of cognitive diagnosis model parameters, we first provide a unified objective function for mini-batch based optimization that can be more efficiently applied to a wide range of models and large datasets.

cognitive diagnosis

ImgTrojan: Jailbreaking Vision-Language Models with ONE Image

1 code implementation5 Mar 2024 Xijia Tao, Shuai Zhong, Lei LI, Qi Liu, Lingpeng Kong

In this paper, we propose a novel jailbreaking attack against VLMs, aiming to bypass their safety barrier when a user inputs harmful instructions.

PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features

1 code implementation4 Mar 2024 Baozhu Zhao, Qiwei Xiong, Xiaohan Zhang, Jingfeng Guo, Qi Liu, Xiaofen Xing, Xiangmin Xu

Three-dimensional point cloud anomaly detection that aims to detect anomaly data points from a training set serves as the foundation for a variety of applications, including industrial inspection and autonomous driving.

Anomaly Detection Autonomous Driving

FreeA: Human-object Interaction Detection using Free Annotation Labels

no code implementations4 Mar 2024 Yuxiao Wang, Zhenao Wei, Xinyu Jiang, Yu Lei, Weiying Xue, Jinxiu Liu, Qi Liu

Recent human-object interaction (HOI) detection approaches rely on high cost of manpower and require comprehensive annotated image datasets.

Human-Object Interaction Detection Object

ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis

no code implementations3 Mar 2024 Mingyue Cheng, Jiqian Yang, Tingyue Pan, Qi Liu, Zhi Li

This paper introduces ConvTimeNet, a novel deep hierarchical fully convolutional network designed to serve as a general-purpose model for time series analysis.

Time Series Time Series Forecasting

Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models

1 code implementation22 Feb 2024 Xudong Lu, Qi Liu, Yuhui Xu, Aojun Zhou, Siyuan Huang, Bo Zhang, Junchi Yan, Hongsheng Li

Specifically, we propose, for the first time to our best knowledge, post-training approaches for task-agnostic and task-specific expert pruning and skipping of MoE LLMs, tailored to improve deployment efficiency while maintaining model performance across a wide range of tasks.

SISSA: Real-time Monitoring of Hardware Functional Safety and Cybersecurity with In-vehicle SOME/IP Ethernet Traffic

1 code implementation21 Feb 2024 Qi Liu, Xingyu Li, Ke Sun, Yufeng Li, Yanchen Liu

Scalable service-Oriented Middleware over IP (SOME/IP) is an Ethernet communication standard protocol in the Automotive Open System Architecture (AUTOSAR), promoting ECU-to-ECU communication over the IP stack.

ViTree: Single-path Neural Tree for Step-wise Interpretable Fine-grained Visual Categorization

no code implementations30 Jan 2024 Danning Lao, Qi Liu, Jiazi Bu, Junchi Yan, Wei Shen

As computer vision continues to advance and finds widespread applications across various domains, the need for interpretability in deep learning models becomes paramount.

Decision Making Fine-Grained Visual Categorization

FedGT: Federated Node Classification with Scalable Graph Transformer

no code implementations26 Jan 2024 Zaixi Zhang, Qingyong Hu, Yang Yu, Weibo Gao, Qi Liu

However, existing methods have the following limitations: (1) The links between local subgraphs are missing in subgraph federated learning.

Classification Federated Learning +2

Red Teaming Visual Language Models

no code implementations23 Jan 2024 Mukai Li, Lei LI, Yuwei Yin, Masood Ahmed, Zhenguang Liu, Qi Liu

Additionally, we simply apply red teaming alignment to LLaVA-v1. 5 with Supervised Fine-tuning (SFT) using RTVLM, and this bolsters the models' performance with 10% in RTVLM test set, 13% in MM-Hal, and without noticeable decline in MM-Bench, overpassing other LLaVA-based models with regular alignment data.


A locally statistical active contour model for SAR image segmentation can be solved by denoising algorithms

no code implementations10 Jan 2024 Guangming Liu, Quanying Sun, Jing Liang, Qi Liu

In this paper, we propose a novel locally statistical variational active contour model based on I-divergence-TV denoising model, which hybrides geodesic active contour (GAC) model with active contours without edges (ACWE) model, and can be used to segment images corrupted by multiplicative gamma noise.

Denoising Image Segmentation +1

LMaaS: Exploring Pricing Strategy of Large Model as a Service for Communication

no code implementations5 Jan 2024 Panlong Wu, Qi Liu, Yanjie Dong, Fangxin Wang

In the first step, we optimize the seller's pricing decision and propose an Iterative Model Pricing (IMP) algorithm that optimizes the prices of large models iteratively by reasoning customers' future rental decisions, which is able to achieve a near-optimal pricing solution.

Intelligent Communication

Unlocking the Potential of Large Language Models for Explainable Recommendations

1 code implementation25 Dec 2023 Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Qi Liu, Enhong Chen

In this study, we propose LLMXRec, a simple yet effective two-stage explainable recommendation framework aimed at further boosting the explanation quality by employing LLMs.

Decision Making Explainable Recommendation +2

Active contours driven by local and global intensity fitting energy with application to SAR image segmentation and its fast solvers

no code implementations19 Dec 2023 Guangming Liu, Qi Liu, Jing Liang, Quanying Sun

In this paper, we propose a novel variational active contour model based on Aubert-Aujol (AA) denoising model, which hybrides geodesic active contour (GAC) model with active contours without edges (ACWE) model and can be used to segment images corrupted by multiplicative gamma noise.

Denoising Image Segmentation +2

Random resistive memory-based deep extreme point learning machine for unified visual processing

no code implementations14 Dec 2023 Shaocong Wang, Yizhao Gao, Yi Li, Woyu Zhang, Yifei Yu, Bo wang, Ning Lin, Hegan Chen, Yue Zhang, Yang Jiang, Dingchen Wang, Jia Chen, Peng Dai, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Xiaoxin Xu, Hayden So, Zhongrui Wang, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks.

AT4CTR: Auxiliary Match Tasks for Enhancing Click-Through Rate Prediction

no code implementations9 Dec 2023 Qi Liu, Xuyang Hou, Defu Lian, Zhe Wang, Haoran Jin, Jia Cheng, Jun Lei

Most existing methods focus on the network architecture design of the CTR model for better accuracy and suffer from the data sparsity problem.

Click-Through Rate Prediction Collaborative Filtering +2

A global optimization SAR image segmentation model can be easily transformed to a general ROF denoising model

no code implementations8 Dec 2023 Guangming Liu, Qi Liu, Jing Liang

The second model is: we use a different splitting approach than one model to transform the global optimization model into a differentiable term and a general ROF model term, which can be solved by the same technique as the first model.

Denoising Image Segmentation +1

SigFormer: Sparse Signal-Guided Transformer for Multi-Modal Human Action Segmentation

1 code implementation29 Nov 2023 Qi Liu, Xinchen Liu, Kun Liu, Xiaoyan Gu, Wu Liu

Nowadays, the majority of approaches concentrate on the fusion of dense signals (i. e., RGB, optical flow, and depth maps).

Action Segmentation Optical Flow Estimation +1

DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding

no code implementations20 Nov 2023 Hao Feng, Qi Liu, Hao liu, Wengang Zhou, Houqiang Li, Can Huang

This work presents DocPedia, a novel large multimodal model (LMM) for versatile OCR-free document understanding, capable of parsing images up to 2, 560$\times$2, 560 resolution.

document understanding Language Modelling +2

Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction

no code implementations15 Nov 2023 Qi Liu, Xuyang Hou, Haoran Jin, Jin Chen, Zhe Wang, Defu Lian, Tan Qu, Jia Cheng, Jun Lei

The insights from this subset reveal the user's decision-making process related to the candidate item, improving prediction accuracy.

Click-Through Rate Prediction

Pruning random resistive memory for optimizing analogue AI

no code implementations13 Nov 2023 Yi Li, Songqi Wang, Yaping Zhao, Shaocong Wang, Woyu Zhang, Yangu He, Ning Lin, Binbin Cui, Xi Chen, Shiming Zhang, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Zhongrui Wang, Xiaoxin Xu, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network.

Audio Classification Image Segmentation +1

Sparse Attention-Based Neural Networks for Code Classification

no code implementations11 Nov 2023 Ziyang Xiang, Zaixi Zhang, Qi Liu

We introduce an approach named the Sparse Attention-based neural network for Code Classification (SACC) in this paper.

Classification Code Classification

Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems

no code implementations1 Nov 2023 Hao Zhang, Mingyue Cheng, Qi Liu, Zhiding Liu, Enhong Chen

Sequential recommender systems (SRS) have gained widespread popularity in recommendation due to their ability to effectively capture dynamic user preferences.

Future prediction Sequential Recommendation

SoulChat: Improving LLMs' Empathy, Listening, and Comfort Abilities through Fine-tuning with Multi-turn Empathy Conversations

no code implementations1 Nov 2023 YiRong Chen, Xiaofen Xing, Jingkai Lin, huimin zheng, Zhenyu Wang, Qi Liu, Xiangmin Xu

Large language models (LLMs) have been widely applied in various fields due to their excellent capability for memorizing knowledge and chain of thought (CoT).

BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT

1 code implementation24 Oct 2023 YiRong Chen, Zhenyu Wang, Xiaofen Xing, huimin zheng, Zhipei Xu, Kai Fang, Junhong Wang, Sihang Li, Jieling Wu, Qi Liu, Xiangmin Xu

Large language models (LLMs) have performed well in providing general and extensive health suggestions in single-turn conversations, exemplified by systems such as ChatGPT, ChatGLM, ChatDoctor, DoctorGLM, and etc.

AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking

1 code implementation NeurIPS 2023 Yang Yu, Qi Liu, Kai Zhang, Yuren Zhang, Chao Song, Min Hou, Yuqing Yuan, Zhihao Ye, Zaixi Zhang, Sanshi Lei Yu

Specifically, we adopt a multiple pairwise ranking loss which trains the user model to capture the similarity orders between the implicitly augmented view, the explicitly augmented view, and views from other users.

Contrastive Learning Data Augmentation

LRRU: Long-short Range Recurrent Updating Networks for Depth Completion

no code implementations ICCV 2023 YuFei Wang, Bo Li, Ge Zhang, Qi Liu, Tao Gao, Yuchao Dai

Existing deep learning-based depth completion methods generally employ massive stacked layers to predict the dense depth map from sparse input data.

Depth Completion

Full-Atom Protein Pocket Design via Iterative Refinement

1 code implementation NeurIPS 2023 Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu

In the initial stage, the residue types and backbone coordinates are refined using a hierarchical context encoder, complemented by two structure refinement modules that capture both inter-residue and pocket-ligand interactions.

Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models

1 code implementation2 Oct 2023 Jean Kaddour, Qi Liu

The in-context learning ability of large language models (LLMs) enables them to generalize to novel downstream tasks with relatively few labeled examples.

Data Augmentation In-Context Learning +4

Leveraging In-the-Wild Data for Effective Self-Supervised Pretraining in Speaker Recognition

1 code implementation21 Sep 2023 Shuai Wang, Qibing Bai, Qi Liu, Jianwei Yu, Zhengyang Chen, Bing Han, Yanmin Qian, Haizhou Li

Current speaker recognition systems primarily rely on supervised approaches, constrained by the scale of labeled datasets.

Speaker Recognition

Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling

1 code implementation19 Sep 2023 Junzhe Jiang, Shang Qu, Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Kai Zhang, Rui Li, Jiatong Li, Min Gao

Recommender systems are indispensable in the realm of online applications, and sequential recommendation has enjoyed considerable prevalence due to its capacity to encapsulate the dynamic shifts in user interests.

Language Modelling Sequential Recommendation +1

FedJudge: Federated Legal Large Language Model

1 code implementation15 Sep 2023 Linan Yue, Qi Liu, Yichao Du, Weibo Gao, Ye Liu, Fangzhou Yao

To this end, in this paper, we propose the first Federated Legal Large Language Model (FedJudge) framework, which fine-tunes Legal LLMs efficiently and effectively.

Continual Learning Federated Learning +2

Beyond Static Datasets: A Deep Interaction Approach to LLM Evaluation

no code implementations8 Sep 2023 Jiatong Li, Rui Li, Qi Liu

Existing LLM evaluation methods are mainly supervised signal-based which depends on static datasets and cannot evaluate the ability of LLMs in dynamic real-world scenarios where deep interaction widely exists.

Code Generation Machine Translation

Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion

no code implementations5 Sep 2023 YuFei Wang, Yuxin Mao, Qi Liu, Yuchao Dai

The decomposed filters not only maintain the favorable properties of guided dynamic filters as being content-dependent and spatially-variant, but also reduce model parameters and hardware costs, as the learned adaptors are decoupled with the number of feature channels.

Depth Completion object-detection +2

Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information

no code implementations1 Sep 2023 Qun Zheng, Xihong Yang, Siwei Wang, Xinru An, Qi Liu

In unsupervised scenarios, deep contrastive multi-view clustering (DCMVC) is becoming a hot research spot, which aims to mine the potential relationships between different views.

Clustering Pseudo Label

Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm

no code implementations1 Sep 2023 Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su

However, we notice that this paradigm leads to the inevitable non-identifiability and explainability overfitting problem, which is harmful to the quantification of learners' cognitive states and the quality of web learning services.

cognitive diagnosis

Research on Image Stitching Based on Invariant Features of Reconstructed Plane

no code implementations30 Aug 2023 Qi Liu, Xiyu Tang, Ju Huo

This paper proposes an image stitching method based on invariant planar features, which uses planar features as constraints to improve the overall effect of natural image stitching.

Image Stitching

Deep Task-specific Bottom Representation Network for Multi-Task Recommendation

no code implementations11 Aug 2023 Qi Liu, Zhilong Zhou, Gangwei Jiang, Tiezheng Ge, Defu Lian

In this paper, we focus on the bottom representation learning of MTL in RS and propose the Deep Task-specific Bottom Representation Network (DTRN) to alleviate the negative transfer problem.

Multi-Task Learning Recommendation Systems +1

FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models

1 code implementation22 Jul 2023 Yuwei Yin, Yazheng Yang, Jian Yang, Qi Liu

To tackle these issues, we propose FinPT and FinBench: the former is a novel approach for financial risk prediction that conduct Profile Tuning on large pretrained foundation models, and the latter is a set of high-quality datasets on financial risks such as default, fraud, and churn.

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

no code implementations18 Jul 2023 Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu, Qi Liu

This research primarily centers on classification and regression tasks involving tabular data, and conducts rigorous experimental testing and analyses to validate the effectiveness of our methodology.

NS4AR: A new, focused on sampling areas sampling method in graphical recommendation Systems

no code implementations13 Jul 2023 Xiangqi Wang, Dilinuer Aishan, Qi Liu

The effectiveness of graphical recommender system depends on the quantity and quality of negative sampling.

Recommendation Systems

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

no code implementations3 Jul 2023 Can Cui, Yaohong Wang, Shunxing Bao, Yucheng Tang, Ruining Deng, Lucas W. Remedios, Zuhayr Asad, Joseph T. Roland, Ken S. Lau, Qi Liu, Lori A. Coburn, Keith T. Wilson, Bennett A. Landman, Yuankai Huo

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training.

Anomaly Detection

A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design

1 code implementation20 Jun 2023 Zaixi Zhang, Jiaxian Yan, Qi Liu, Enhong Chen, Marinka Zitnik

Recent developments in geometric deep learning, focusing on the integration and processing of 3D geometric data, coupled with the availability of accurate protein 3D structure predictions from tools like AlphaFold, have greatly advanced the field of structure-based drug design.

Benchmarking Drug Discovery +1

Efficiently Measuring the Cognitive Ability of LLMs: An Adaptive Testing Perspective

1 code implementation18 Jun 2023 Yan Zhuang, Qi Liu, Yuting Ning, Weizhe Huang, Rui Lv, Zhenya Huang, Guanhao Zhao, Zheng Zhang, Qingyang Mao, Shijin Wang, Enhong Chen

Different tests for different models using efficient adaptive testing -- we believe this has the potential to become a new norm in evaluating large language models.

Mathematical Reasoning

Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation

no code implementations14 Jun 2023 Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen

Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.

Attribute Knowledge Graphs +2

MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer

1 code implementation12 Jun 2023 Yazheng Yang, Zhou Zhao, Qi Liu

Our proposed method addresses this issue by assigning individual style vector to each token in a text, allowing for fine-grained control and manipulation of the style strength.

Style Transfer Text Style Transfer +1

Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction

1 code implementation8 Jun 2023 Jiaxian Yan, Zhaofeng Ye, ZiYi Yang, Chengqiang Lu, Shengyu Zhang, Qi Liu, Jiezhong Qiu

By introducing multi-task pre-training to treat the prediction of different affinity labels as different tasks and classifying relative rankings between samples from the same bioassay, MBP learns robust and transferrable structural knowledge from our new ChEMBL-Dock dataset with varied and noisy labels.

Drug Discovery

M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning

no code implementations7 Jun 2023 Lei LI, Yuwei Yin, Shicheng Li, Liang Chen, Peiyi Wang, Shuhuai Ren, Mukai Li, Yazheng Yang, Jingjing Xu, Xu sun, Lingpeng Kong, Qi Liu

To tackle this challenge and promote research in the vision-language field, we introduce the Multi-Modal, Multilingual Instruction Tuning (M$^3$IT) dataset, designed to optimize VLM alignment with human instructions.

World Knowledge

A Survey on Large Language Models for Recommendation

1 code implementation31 May 2023 Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, HengShu Zhu, Qi Liu, Hui Xiong, Enhong Chen

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS).

Recommendation Systems Self-Supervised Learning

Large Language Models are not Fair Evaluators

1 code implementation29 May 2023 Peiyi Wang, Lei LI, Liang Chen, Zefan Cai, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, Zhifang Sui

In this paper, we uncover a systematic bias in the evaluation paradigm of adopting large language models~(LLMs), e. g., GPT-4, as a referee to score and compare the quality of responses generated by candidate models.

Language Modelling Large Language Model +1

Can Language Models Understand Physical Concepts?

1 code implementation23 May 2023 Lei LI, Jingjing Xu, Qingxiu Dong, Ce Zheng, Qi Liu, Lingpeng Kong, Xu sun

Language models~(LMs) gradually become general-purpose interfaces in the interactive and embodied world, where the understanding of physical concepts is an essential prerequisite.

Rethinking Speech Recognition with A Multimodal Perspective via Acoustic and Semantic Cooperative Decoding

no code implementations23 May 2023 Tian-Hao Zhang, Hai-Bo Qin, Zhi-Hao Lai, Song-Lu Chen, Qi Liu, Feng Chen, Xinyuan Qian, Xu-Cheng Yin

The experimental results show that ASCD significantly improves the performance by leveraging both the acoustic and semantic information cooperatively.

speech-recognition Speech Recognition

Interactive Natural Language Processing

no code implementations22 May 2023 Zekun Wang, Ge Zhang, Kexin Yang, Ning Shi, Wangchunshu Zhou, Shaochun Hao, Guangzheng Xiong, Yizhi Li, Mong Yuan Sim, Xiuying Chen, Qingqing Zhu, Zhenzhu Yang, Adam Nik, Qi Liu, Chenghua Lin, Shi Wang, Ruibo Liu, Wenhu Chen, Ke Xu, Dayiheng Liu, Yike Guo, Jie Fu

Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within the field of NLP, aimed at addressing limitations in existing frameworks while aligning with the ultimate goals of artificial intelligence.

Decision Making

NIKI: Neural Inverse Kinematics with Invertible Neural Networks for 3D Human Pose and Shape Estimation

1 code implementation CVPR 2023 Jiefeng Li, Siyuan Bian, Qi Liu, Jiasheng Tang, Fan Wang, Cewu Lu

In this work, we present NIKI (Neural Inverse Kinematics with Invertible Neural Network), which models bi-directional errors to improve the robustness to occlusions and obtain pixel-aligned accuracy.

3D human pose and shape estimation

An Equivariant Generative Framework for Molecular Graph-Structure Co-Design

no code implementations12 Apr 2023 Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen

Our extensive investigation reveals that the 2D topology and 3D geometry contain intrinsically complementary information in molecule design, and provide new insights into machine learning-based molecule representation and generation.

Drug Discovery Graph Generation +1

Quiz-based Knowledge Tracing

no code implementations5 Apr 2023 Shuanghong Shen, Enhong Chen, Bihan Xu, Qi Liu, Zhenya Huang, Linbo Zhu, Yu Su

In this paper, we present the Quiz-based Knowledge Tracing (QKT) model to monitor students' knowledge states according to their quiz-based learning interactions.

Decision Making Knowledge Tracing

Two Heads are Better than One: A Bio-inspired Method for Improving Classification on EEG-ET Data

no code implementations25 Mar 2023 Eric Modesitt, Ruiqi Yang, Qi Liu

Classifying EEG data is integral to the performance of Brain Computer Interfaces (BCI) and their applications.

EEG feature selection

Backdoor Defense via Deconfounded Representation Learning

1 code implementation CVPR 2023 Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu, Qingyong Hu

The other clean model dedicates to capturing the desired causal effects by minimizing the mutual information with the confounding representations from the backdoored model and employing a sample-wise re-weighting scheme.

Backdoor Attack backdoor defense +1

TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders

1 code implementation1 Mar 2023 Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Enhong Chen

In this work, we propose TimeMAE, a novel self-supervised paradigm for learning transferrable time series representations based on transformer networks.

Time Series Time Series Analysis +1

Retrieved Sequence Augmentation for Protein Representation Learning

1 code implementation24 Feb 2023 Chang Ma, Haiteng Zhao, Lin Zheng, Jiayi Xin, Qintong Li, Lijun Wu, Zhihong Deng, Yang Lu, Qi Liu, Lingpeng Kong

RSA links query protein sequences to a set of sequences with similar structures or properties in the database and combines these sequences for downstream prediction.

Property Prediction Representation Learning +1

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges

no code implementations20 Feb 2023 Qi Liu, ZhiYun Yang, Ru Ji, Yonghong Zhang, Muhammad Bilal, Xiaodong Liu, S Vimal, Xiaolong Xu

Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting.

FormerTime: Hierarchical Multi-Scale Representations for Multivariate Time Series Classification

no code implementations20 Feb 2023 Mingyue Cheng, Qi Liu, Zhiding Liu, Zhi Li, Yucong Luo, Enhong Chen

Deep learning-based algorithms, e. g., convolutional networks, have significantly facilitated multivariate time series classification (MTSC) task.

Time Series Time Series Analysis +1

Search-Engine-augmented Dialogue Response Generation with Cheaply Supervised Query Production

1 code implementation16 Feb 2023 Ante Wang, Linfeng Song, Qi Liu, Haitao Mi, Longyue Wang, Zhaopeng Tu, Jinsong Su, Dong Yu

We propose a dialogue model that can access the vast and dynamic information from any search engine for response generation.

Chatbot Response Generation

Learning by Applying: A General Framework for Mathematical Reasoning via Enhancing Explicit Knowledge Learning

no code implementations11 Feb 2023 Jiayu Liu, Zhenya Huang, ChengXiang Zhai, Qi Liu

In LeAp, we perform knowledge learning in a novel problem-knowledge-expression paradigm, with a Knowledge Encoder to acquire knowledge from problem data and a Knowledge Decoder to apply knowledge for expression reasoning.

Mathematical Reasoning

ShapeWordNet: An Interpretable Shapelet Neural Network for Physiological Signal Classification

no code implementations10 Feb 2023 Wenqiang He, Mingyue Cheng, Qi Liu, Zhi Li

Physiological signals are high-dimensional time series of great practical values in medical and healthcare applications.

Contrastive Learning Time Series +1

A Novel Approach for Auto-Formulation of Optimization Problems

no code implementations9 Feb 2023 Yuting Ning, Jiayu Liu, Longhu Qin, Tong Xiao, Shangzi Xue, Zhenya Huang, Qi Liu, Enhong Chen, Jinze Wu

In the Natural Language for Optimization (NL4Opt) NeurIPS 2022 competition, competitors focus on improving the accessibility and usability of optimization solvers, with the aim of subtask 1: recognizing the semantic entities that correspond to the components of the optimization problem; subtask 2: generating formulations for the optimization problem.

Ensemble Learning named-entity-recognition +2

N-Gram Nearest Neighbor Machine Translation

no code implementations30 Jan 2023 Rui Lv, Junliang Guo, Rui Wang, Xu Tan, Qi Liu, Tao Qin

Nearest neighbor machine translation augments the Autoregressive Translation~(AT) with $k$-nearest-neighbor retrieval, by comparing the similarity between the token-level context representations of the target tokens in the query and the datastore.

Domain Adaptation Machine Translation +2

Joint Appearance and Motion Learning for Efficient Rolling Shutter Correction

1 code implementation CVPR 2023 Bin Fan, Yuxin Mao, Yuchao Dai, Zhexiong Wan, Qi Liu

Rolling shutter correction (RSC) is becoming increasingly popular for RS cameras that are widely used in commercial and industrial applications.

Data Augmentation Rolling Shutter Correction

Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense

1 code implementation11 Dec 2022 Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, Zaixi Zhang

Experiments on two public datasets show that ClusterAttack can effectively degrade the performance of FedRec systems while circumventing many defense methods, and UNION can improve the resistance of the system against various untargeted attacks, including our ClusterAttack.

Contrastive Learning Recommendation Systems

Progressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds

no code implementations30 Nov 2022 Qi Liu, Yiyun Liu, Honglei Su, Hui Yuan, Raouf Hamzaoui

In this paper, a progressive knowledge transfer based on human visual perception mechanism for perceptual quality assessment of point clouds (PKT-PCQA) is proposed.

Transfer Learning

Nested Named Entity Recognition from Medical Texts: An Adaptive Shared Network Architecture with Attentive CRF

no code implementations9 Nov 2022 Junzhe Jiang, Mingyue Cheng, Qi Liu, Zhi Li, Enhong Chen

Recognizing useful named entities plays a vital role in medical information processing, which helps drive the development of medical area research.

Medical Named Entity Recognition named-entity-recognition +3

One Person, One Model--Learning Compound Router for Sequential Recommendation

1 code implementation5 Nov 2022 Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen

The core idea of CANet is to route the input user behaviors with a light-weighted router module.

Sequential Recommendation

Searching Dense Point Correspondences via Permutation Matrix Learning

no code implementations26 Oct 2022 Zhiyuan Zhang, Jiadai Sun, Yuchao Dai, Bin Fan, Qi Liu

In response, this paper presents a novel end-to-end learning-based method to estimate the dense correspondence of 3D point clouds, in which the problem of point matching is formulated as a zero-one assignment problem to achieve a permutation matching matrix to implement the one-to-one principle fundamentally.

CU-Net: LiDAR Depth-Only Completion With Coupled U-Net

1 code implementation26 Oct 2022 YuFei Wang, Yuchao Dai, Qi Liu, Peng Yang, Jiadai Sun, Bo Li

We find that existing depth-only methods can obtain satisfactory results in the areas where the measurement points are almost accurate and evenly distributed (denoted as normal areas), while the performance is limited in the areas where the foreground and background points are overlapped due to occlusion (denoted as overlap areas) and the areas where there are no measurement points around (denoted as blank areas) since the methods have no reliable input information in these areas.

Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play

1 code implementation21 Oct 2022 Qi Liu, Zihuiwen Ye, Tao Yu, Phil Blunsom, Linfeng Song

We first design a SQL-to-text model conditioned on a sampled goal query, which represents a user's intent, that then converses with a text-to-SQL semantic parser to generate new interactions.

Domain Generalization SQL-to-Text +1

Hierarchical Graph Transformer with Adaptive Node Sampling

1 code implementation8 Oct 2022 Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee

The Transformer architecture has achieved remarkable success in a number of domains including natural language processing and computer vision.

Model Inversion Attacks against Graph Neural Networks

no code implementations16 Sep 2022 Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen

One famous privacy attack against data analysis models is the model inversion attack, which aims to infer sensitive data in the training dataset and leads to great privacy concerns.

Reinforcement Learning (RL)

Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images

1 code implementation15 Aug 2022 Ruining Deng, Can Cui, Lucas W. Remedios, Shunxing Bao, R. Michael Womick, Sophie Chiron, Jia Li, Joseph T. Roland, Ken S. Lau, Qi Liu, Keith T. Wilson, Yaohong Wang, Lori A. Coburn, Bennett A. Landman, Yuankai Huo

Multi-instance learning (MIL) is widely used in the computer-aided interpretation of pathological Whole Slide Images (WSIs) to solve the lack of pixel-wise or patch-wise annotations.

whole slide images

Causal Machine Learning: A Survey and Open Problems

no code implementations30 Jun 2022 Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva

Causal Machine Learning (CausalML) is an umbrella term for machine learning methods that formalize the data-generation process as a structural causal model (SCM).

BIG-bench Machine Learning Fairness +1

Evaluating Self-Supervised Learning for Molecular Graph Embeddings

1 code implementation NeurIPS 2023 Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu

Graph Self-Supervised Learning (GSSL) provides a robust pathway for acquiring embeddings without expert labelling, a capability that carries profound implications for molecular graphs due to the staggering number of potential molecules and the high cost of obtaining labels.

Self-Supervised Learning

Context-Aware Video Reconstruction for Rolling Shutter Cameras

1 code implementation CVPR 2022 Bin Fan, Yuchao Dai, Zhiyuan Zhang, Qi Liu, Mingyi He

Then, a refinement scheme is proposed to guide the GS frame synthesis along with bilateral occlusion masks to produce high-fidelity GS video frames at arbitrary times.

Motion Compensation Video Reconstruction

Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

no code implementations18 May 2022 Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen

Existing studies in this task attach more attention to the sequence modeling of sentences while largely ignoring the rich domain-invariant semantics embedded in graph structures (i. e., the part-of-speech tags and dependency relations).

Classification Graph Attention +4

A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles

1 code implementation22 Feb 2022 Jingyi Xu, Zirui Li, Li Gao, Junyi Ma, Qi Liu, Yanan Zhao

Different exploration methods of DRL, including adding action space noise and parameter space noise, are compared against each other in the transfer learning process in this work.

energy management Management +3

Ligandformer: A Graph Neural Network for Predicting Compound Property with Robust Interpretation

no code implementations21 Feb 2022 Jinjiang Guo, Qi Liu, Han Guo, Xi Lu

Robust and efficient interpretation of QSAR methods is quite useful to validate AI prediction rationales with subjective opinion (chemist or biologist expertise), understand sophisticated chemical or biological process mechanisms, and provide heuristic ideas for structure optimization in pharmaceutical industry.

Low-Rank and Row-Sparse Decomposition for Joint DOA Estimation and Distorted Sensor Detection

no code implementations2 Feb 2022 Huiping Huang, Qi Liu, Hing Cheung So, Abdelhak M. Zoubir

Distorted sensors could occur randomly and may lead to the breakdown of a sensor array system.

Relational Memory Augmented Language Models

no code implementations24 Jan 2022 Qi Liu, Dani Yogatama, Phil Blunsom

We present a memory-augmented approach to condition an autoregressive language model on a knowledge graph.

Language Modelling Text Generation

Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction

1 code implementation30 Dec 2021 Zhenguang Liu, Shuang Wu, Shuyuan Jin, Shouling Ji, Qi Liu, Shijian Lu, Li Cheng

One aspect that has been obviated so far, is the fact that how we represent the skeletal pose has a critical impact on the prediction results.

motion prediction

Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation

1 code implementation2 Dec 2021 Yang Yu, Fangzhao Wu, Chuhan Wu, Jingwei Yi, Qi Liu

We further propose a two-stage knowledge distillation method to improve the efficiency of the large PLM-based news recommendation model while maintaining its performance.

Knowledge Distillation Natural Language Understanding +1

ProtGNN: Towards Self-Explaining Graph Neural Networks

1 code implementation2 Dec 2021 Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Cheekong Lee

In this work, we propose Prototype Graph Neural Network (ProtGNN), which combines prototype learning with GNNs and provides a new perspective on the explanations of GNNs.

Contrastive Cross-domain Recommendation in Matching

1 code implementation2 Dec 2021 Ruobing Xie, Qi Liu, Liangdong Wang, Shukai Liu, Bo Zhang, Leyu Lin

Cross-domain recommendation (CDR) aims to provide better recommendation results in the target domain with the help of the source domain, which is widely used and explored in real-world systems.

Contrastive Learning Representation Learning +1

Nonlinear Tensor Ring Network

no code implementations12 Nov 2021 Xiao Peng Li, Qi Liu, Hing Cheung So

Experimental results demonstrate the effectiveness and superiority of the proposed NTRN for image classification using two basic neural networks, LeNet-5 and VGG-11 on three datasets, viz.

Image Classification

Perceptual Quality Assessment of Colored 3D Point Clouds

1 code implementation10 Nov 2021 Honglei Su, Qi Liu, Zhengfang Duanmu, Wentao Liu, Zhou Wang

In this work, we first build a large 3D point cloud database for subjective and objective quality assessment of point clouds.

Point Cloud Quality Assessment

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction

1 code implementation NeurIPS 2021 Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee

To bridge this gap, we propose Motif-based Graph Self-supervised Learning (MGSSL) by introducing a novel self-supervised motif generation framework for GNNs.

Molecular Property Prediction Property Prediction +2

DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis

1 code implementation ICCV 2021 Shulan Ruan, Yong Zhang, Kun Zhang, Yanbo Fan, Fan Tang, Qi Liu, Enhong Chen

Text-to-image synthesis refers to generating an image from a given text description, the key goal of which lies in photo realism and semantic consistency.

Image Generation Sentence +2

SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation

no code implementations18 Aug 2021 Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen

Specifically, we first encode user/item reviews via BERT and propose a light-weighted sentiment learner to extract semantic features of each review.

Recommendation Systems

LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching

no code implementations6 Aug 2021 Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Meng Wang

In order to overcome this problem and boost the performance of attention mechanism, we propose a novel dynamic re-read attention, which can pay close attention to one small region of sentences at each step and re-read the important parts for better sentence representations.

Language Modelling Natural Language Inference +2

Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlook

no code implementations2 Jul 2021 Qi Liu, Xueyuan Li, Shihua Yuan, Zirui Li

Autonomous vehicles have a great potential in the application of both civil and military fields, and have become the focus of research with the rapid development of science and economy.

Autonomous Vehicles Decision Making

GraphMI: Extracting Private Graph Data from Graph Neural Networks

1 code implementation5 Jun 2021 Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen

Then we design a graph auto-encoder module to efficiently exploit graph topology, node attributes, and target model parameters for edge inference.

Hybrid attention network based on progressive embedding scale-context for crowd counting

no code implementations4 Jun 2021 Fusen Wang, Jun Sang, Zhongyuan Wu, Qi Liu, Nong Sang

In this paper, we propose a Hybrid Attention Network (HAN) by employing Progressive Embedding Scale-context (PES) information, which enables the network to simultaneously suppress noise and adapt head scale variation.

Crowd Counting

Causal Effect Inference for Structured Treatments

2 code implementations NeurIPS 2021 Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J. Kusner, Ricardo Silva

We address the estimation of conditional average treatment effects (CATEs) for structured treatments (e. g., graphs, images, texts).

Estimating Fund-Raising Performance for Start-up Projects from a Market Graph Perspective

no code implementations27 May 2021 Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Enhong Chen

Usually, this prediction is always with great challenges to making a comprehensive understanding of both the start-up project and market environment.

Cardiac Functional Analysis with Cine MRI via Deep Learning Reconstruction

no code implementations17 May 2021 Eric Z. Chen, Xiao Chen, Jingyuan Lyu, Qi Liu, Zhongqi Zhang, Yu Ding, Shuheng Zhang, Terrence Chen, Jian Xu, Shanhui Sun

To the best of our knowledge, this is the first work to evaluate the cine MRI with deep learning reconstruction for cardiac function analysis and compare it with other conventional methods.

A Survey of Knowledge Tracing: Models, Variants, and Applications

1 code implementation6 May 2021 Shuanghong Shen, Qi Liu, Zhenya Huang, Yonghe Zheng, Minghao Yin, Minjuan Wang, Enhong Chen

We hope that the current survey will assist both researchers and practitioners in fostering the development of KT, thereby benefiting a broader range of students.

Knowledge Tracing

XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction

1 code implementation22 Apr 2021 Runlong Yu, Yuyang Ye, Qi Liu, Zihan Wang, Chunfeng Yang, Yucheng Hu, Enhong Chen

Motivated by this, we propose a novel Extreme Cross Network, abbreviated XCrossNet, which aims at learning dense and sparse feature interactions in an explicit manner.

Click-Through Rate Prediction Feature Engineering +1

Pretraining the Noisy Channel Model for Task-Oriented Dialogue

no code implementations18 Mar 2021 Qi Liu, Lei Yu, Laura Rimell, Phil Blunsom

Direct decoding for task-oriented dialogue is known to suffer from the explaining-away effect, manifested in models that prefer short and generic responses.

End-To-End Dialogue Modelling

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

2 code implementations24 Feb 2021 Yang You, Yujing Lou, Ruoxi Shi, Qi Liu, Yu-Wing Tai, Lizhuang Ma, Weiming Wang, Cewu Lu

Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point.

3D Feature Matching Data Augmentation

NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application

no code implementations Findings (EMNLP) 2021 Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Qi Liu

However, existing language models are pre-trained and distilled on general corpus like Wikipedia, which has some gaps with the news domain and may be suboptimal for news intelligence.

Knowledge Distillation Language Modelling +2

Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network

no code implementations7 Feb 2021 Ruobing Xie, Qi Liu, Shukai Liu, Ziwei Zhang, Peng Cui, Bo Zhang, Leyu Lin

In this paper, we propose a novel Heterogeneous graph neural network framework for diversified recommendation (GraphDR) in matching to improve both recommendation accuracy and diversity.

Graph Attention Recommendation Systems

Scenario Generation for Cooling, Heating, and Power Loads Using Generative Moment Matching Networks

no code implementations5 Feb 2021 Wenlong Liao, Yusen Wang, Yuelong Wang, Kody Powell, Qi Liu, Zhe Yang

Scenario generations of cooling, heating, and power loads are of great significance for the economic operation and stability analysis of integrated energy systems.

Learning the Implicit Semantic Representation on Graph-Structured Data

1 code implementation16 Jan 2021 Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Jun Wang, Mengdi Zhang, Enhong Chen

Existing representation learning methods in graph convolutional networks are mainly designed by describing the neighborhood of each node as a perceptual whole, while the implicit semantic associations behind highly complex interactions of graphs are largely unexploited.

Representation Learning

Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing

no code implementations15 Jan 2021 Haoyang Bi, Haiping Ma, Zhenya Huang, Yu Yin, Qi Liu, Enhong Chen, Yu Su, Shijin Wang

In this paper, we study a novel model-agnostic CAT problem, where we aim to propose a flexible framework that can adapt to different cognitive models.

Active Learning

Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction

no code implementations13 Dec 2020 Kai Zhang, Hao Qian, Qing Cui, Qi Liu, Longfei Li, Jun Zhou, Jianhui Ma, Enhong Chen

In the Click-Through Rate (CTR) prediction scenario, user's sequential behaviors are well utilized to capture the user interest in the recent literature.

Click-Through Rate Prediction