Search Results for author: Qi Zhang

Found 288 papers, 112 papers with code

A Progressive Framework for Role-Aware Rumor Resolution

1 code implementation COLING 2022 Lei Chen, Guanying Li, Zhongyu Wei, Yang Yang, Baohua Zhou, Qi Zhang, Xuanjing Huang

Existing works on rumor resolution have shown great potential in recognizing word appearance and user participation.

PlugAT: A Plug and Play Module to Defend against Textual Adversarial Attack

no code implementations COLING 2022 Rui Zheng, Rong Bao, Qin Liu, Tao Gui, Qi Zhang, Xuanjing Huang, Rui Xie, Wei Wu

To reduce the potential side effects of using defense modules, we further propose a novel forgetting restricted adversarial training, which filters out bad adversarial examples that impair the performance of original ones.

Adversarial Attack Domain Adaptation +2

LFKQG: A Controlled Generation Framework with Local Fine-tuning for Question Generation over Knowledge Bases

no code implementations COLING 2022 Zichu Fei, Xin Zhou, Tao Gui, Qi Zhang, Xuanjing Huang

Existing KBQG models still face two main challenges: (1) Most models often focus on the most relevant part of the answer entity, while neglecting the rest of the subgraph.

Natural Questions Question Generation +1

Read Extensively, Focus Smartly: A Cross-document Semantic Enhancement Method for Visual Documents NER

no code implementations COLING 2022 Jun Zhao, Xin Zhao, WenYu Zhan, Tao Gui, Qi Zhang, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu

To deal with this problem, this work proposes a cross-document semantic enhancement method, which consists of two modules: 1) To prevent distractions from irrelevant regions in the current document, we design a learnable attention mask mechanism, which is used to adaptively filter redundant information in the current document.


An Empirical Assessment of the Qualitative Aspects of Misinformation in Health News

no code implementations NAACL (NLP4IF) 2021 Chaoyuan Zuo, Qi Zhang, Ritwik Banerjee

We present a health news classification task to determine whether medical news articles satisfy a set of review criteria deemed important by medical experts and health care journalists.

Fact Checking Misinformation +1

CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation

1 code implementation ACL 2022 Zichu Fei, Qi Zhang, Tao Gui, Di Liang, Sirui Wang, Wei Wu, Xuanjing Huang

CQG employs a simple method to generate the multi-hop questions that contain key entities in multi-hop reasoning chains, which ensure the complexity and quality of the questions.

Question Generation Question-Generation

Iterative GNN-based Decoder for Question Generation

1 code implementation EMNLP 2021 Zichu Fei, Qi Zhang, Yaqian Zhou

However, (1) they ignore the rich structure information that is hidden in the previously generated text.

Question Generation Question-Generation

Making Parameter-efficient Tuning More Efficient: A Unified Framework for Classification Tasks

1 code implementation COLING 2022 Xin Zhou, Ruotian Ma, Yicheng Zou, Xuanting Chen, Tao Gui, Qi Zhang, Xuanjing Huang, Rui Xie, Wei Wu

Specifically, we re-formulate both token and sentence classification tasks into a unified language modeling task, and map label spaces of different tasks into the same vocabulary space.

Language Modelling Sentence Classification +1

A Structure-Aware Argument Encoder for Literature Discourse Analysis

1 code implementation COLING 2022 Yinzi Li, Wei Chen, Zhongyu Wei, Yujun Huang, Chujun Wang, Siyuan Wang, Qi Zhang, Xuanjing Huang, Libo Wu

Existing research for argument representation learning mainly treats tokens in the sentence equally and ignores the implied structure information of argumentative context.

Representation Learning

Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail

no code implementations19 Sep 2023 Yiyu Zhuang, Qi Zhang, Ying Feng, Hao Zhu, Yao Yao, Xiaoyu Li, Yan-Pei Cao, Ying Shan, Xun Cao

Drawing inspiration from voxel-based representations with the level of detail (LoD), we introduce a multi-scale tri-plane-based scene representation that is capable of capturing the LoD of the signed distance function (SDF) and the space radiance.

Surface Reconstruction

Syntax Tree Constrained Graph Network for Visual Question Answering

no code implementations17 Sep 2023 Xiangrui Su, Qi Zhang, Chongyang Shi, Jiachang Liu, Liang Hu

Existing VQA methods integrate vision modeling and language understanding to explore the deep semantics of the question.

Question Answering Visual Question Answering

Cure the headache of Transformers via Collinear Constrained Attention

1 code implementation15 Sep 2023 Shiyi Zhu, Jing Ye, Wei Jiang, Qi Zhang, Yifan Wu, Jianguo Li

As the rapid progression of practical applications based on Large Language Models continues, the importance of extrapolating performance has grown exponentially in the research domain.

One-Bit-Aided Modulo Sampling for DOA Estimation

no code implementations10 Sep 2023 Qi Zhang, Jiang Zhu, Zhiwei Xu, De Wen Soh

To overcome this fundamental bottleneck, we propose a one-bit-aided (1bit-aided) modulo sampling scheme for direction-of-arrival (DOA) estimation.


VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generation

no code implementations1 Sep 2023 Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, Jingdong Wang

In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion.

Text-to-Video Generation Video Generation

${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

1 code implementation23 Aug 2023 Dingyang Chen, Qi Zhang

Identification and analysis of symmetrical patterns in the natural world have led to significant discoveries across various scientific fields, such as the formulation of gravitational laws in physics and advancements in the study of chemical structures.

Inductive Bias Multi-agent Reinforcement Learning +2

Data-driven decision-focused surrogate modeling

1 code implementation23 Aug 2023 Rishabh Gupta, Qi Zhang

We introduce the concept of decision-focused surrogate modeling for solving computationally challenging nonlinear optimization problems in real-time settings.

No-frills Temporal Video Grounding: Multi-Scale Neighboring Attention and Zoom-in Boundary Detection

no code implementations20 Jul 2023 Qi Zhang, Sipeng Zheng, Qin Jin

Temporal video grounding (TVG) aims to retrieve the time interval of a language query from an untrimmed video.

Boundary Detection Video Grounding

A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics

no code implementations3 Jul 2023 Chuan Qin, Le Zhang, Rui Zha, Dazhong Shen, Qi Zhang, Ying Sun, Chen Zhu, HengShu Zhu, Hui Xiong

To this end, we present an up-to-date and comprehensive survey on AI technologies used for talent analytics in the field of human resource management.

Decision Making Management

On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection

1 code implementation27 Jun 2023 Songyang Gao, Shihan Dou, Qi Zhang, Xuanjing Huang, Jin Ma, Ying Shan

Detecting adversarial samples that are carefully crafted to fool the model is a critical step to socially-secure applications.

text-classification Text Classification

DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization

1 code implementation27 Jun 2023 Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan

Adversarial training is one of the best-performing methods in improving the robustness of deep language models.

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference

no code implementations26 Jun 2023 Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang

Deploying pre-trained transformer models like BERT on downstream tasks in resource-constrained scenarios is challenging due to their high inference cost, which grows rapidly with input sequence length.

Model Compression

Successive one-sided Hodrick-Prescott filter with incremental filtering algorithm for nonlinear economic time series

no code implementations17 Jun 2023 Yuxia Liu, Qi Zhang, Wei Xiao, Tianguang Chu

We propose a successive one-sided Hodrick-Prescott (SOHP) filter from multiple time scale decomposition perspective to derive trend estimate for a time series.

Time Series

Process Knowledge-infused Learning for Clinician-friendly Explanations

no code implementations16 Jun 2023 Kaushik Roy, Yuxin Zi, Manas Gaur, Jinendra Malekar, Qi Zhang, Vignesh Narayanan, Amit Sheth

In this study, we introduce Process Knowledge-infused Learning (PK-iL), a new learning paradigm that layers clinical process knowledge structures on language model outputs, enabling clinician-friendly explanations of the underlying language model predictions.

Explainable Artificial Intelligence (XAI) Language Modelling

Open Set Relation Extraction via Unknown-Aware Training

1 code implementation8 Jun 2023 Jun Zhao, Xin Zhao, WenYu Zhan, Qi Zhang, Tao Gui, Zhongyu Wei, Yunwen Chen, Xiang Gao, Xuanjing Huang

Inspired by text adversarial attacks, we adaptively apply small but critical perturbations to original training instances and thus synthesizing negative instances that are more likely to be mistaken by the model as known relations.

Relation Extraction

On the Generalization of Multi-modal Contrastive Learning

1 code implementation7 Jun 2023 Qi Zhang, Yifei Wang, Yisen Wang

Multi-modal contrastive learning (MMCL) has recently garnered considerable interest due to its superior performance in visual tasks, achieved by embedding multi-modal data, such as visual-language pairs.

Contrastive Learning

Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

1 code implementation2 Jun 2023 Dingyang Chen, Qi Zhang

Executing actions in a correlated manner is a common strategy for human coordination that often leads to better cooperation, which is also potentially beneficial for cooperative multi-agent reinforcement learning (MARL).

Multi-agent Reinforcement Learning

Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network

no code implementations31 May 2023 Yan Wang, Feng Shu, Zhihong Zhuang, Rongen Dong, Qi Zhang, Di wu, Liang Yang, Jiangzhou Wang

Numerical simulation results show that a 3-bit discrete phase shifter is required to achieve a trivial performance loss for a large-scale active IRS.


Towards Better Entity Linking with Multi-View Enhanced Distillation

1 code implementation27 May 2023 Yi Liu, Yuan Tian, Jianxun Lian, Xinlong Wang, Yanan Cao, Fang Fang, Wen Zhang, Haizhen Huang, Denvy Deng, Qi Zhang

Aiming at learning entity representations that can match divergent mentions, this paper proposes a Multi-View Enhanced Distillation (MVD) framework, which can effectively transfer knowledge of multiple fine-grained and mention-relevant parts within entities from cross-encoders to dual-encoders.

Entity Linking Knowledge Distillation +1

Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement

1 code implementation23 May 2023 Zhiheng Xi, Senjie Jin, Yuhao Zhou, Rui Zheng, Songyang Gao, Tao Gui, Qi Zhang, Xuanjing Huang

For example, with Text-davinci-003, our method boosts the performance of standard few-shot prompting by $8. 0\%$ on GSM8K and $17. 8\%$ on MultiArith; it also improves the performance of CoT by $6. 0\%$ on GSM8K and $6. 0\%$ on MathQA, respectively.


Causal Intervention for Abstractive Related Work Generation

no code implementations23 May 2023 Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Ivor Tsang

Abstractive related work generation has attracted increasing attention in generating coherent related work that better helps readers grasp the background in the current research.

Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs

1 code implementation23 May 2023 Siyuan Wang, Zhongyu Wei, Meng Han, Zhihao Fan, Haijun Shan, Qi Zhang, Xuanjing Huang

The results demonstrate the effectiveness of our method on logical reasoning over KGs in both inductive and transductive settings.

Knowledge Graphs Logical Reasoning

A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition

1 code implementation21 May 2023 Limao Xiong, Jie zhou, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan

Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.

named-entity-recognition Named Entity Recognition +2

Movie101: A New Movie Understanding Benchmark

1 code implementation20 May 2023 Zihao Yue, Qi Zhang, Anwen Hu, Liang Zhang, Ziheng Wang, Qin Jin

Closer to real scenarios, the Movie Clip Narrating (MCN) task in our benchmark asks models to generate role-aware narration paragraphs for complete movie clips where no actors are speaking.

Video Captioning

Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization

1 code implementation20 May 2023 Ting Wu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang

Models trained with empirical risk minimization (ERM) are revealed to easily rely on spurious correlations, resulting in poor generalization.

Out-of-Distribution Generalization text-classification +1

DMDD: A Large-Scale Dataset for Dataset Mentions Detection

no code implementations19 May 2023 Huitong Pan, Qi Zhang, Eduard Dragut, Cornelia Caragea, Longin Jan Latecki

We use DMDD to establish baseline performance for dataset mention detection and linking.

Accurate Gigapixel Crowd Counting by Iterative Zooming and Refinement

no code implementations16 May 2023 Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

The increasing prevalence of gigapixel resolutions has presented new challenges for crowd counting.

Crowd Counting

Dual-Alignment Pre-training for Cross-lingual Sentence Embedding

1 code implementation16 May 2023 Ziheng Li, Shaohan Huang, Zihan Zhang, Zhi-Hong Deng, Qiang Lou, Haizhen Huang, Jian Jiao, Furu Wei, Weiwei Deng, Qi Zhang

Recent studies have shown that dual encoder models trained with the sentence-level translation ranking task are effective methods for cross-lingual sentence embedding.

Language Modelling Sentence Embedding +2

Maybe Only 0.5% Data is Needed: A Preliminary Exploration of Low Training Data Instruction Tuning

no code implementations16 May 2023 Hao Chen, Yiming Zhang, Qi Zhang, Hantao Yang, Xiaomeng Hu, Xuetao Ma, Yifan Yanggong, Junbo Zhao

Instruction tuning for large language models (LLMs) has gained attention from researchers due to its ability to unlock the potential of LLMs in following instructions.

Pre-training Language Model as a Multi-perspective Course Learner

no code implementations6 May 2023 Beiduo Chen, Shaohan Huang, Zihan Zhang, Wu Guo, ZhenHua Ling, Haizhen Huang, Furu Wei, Weiwei Deng, Qi Zhang

Besides, two self-correction courses are proposed to bridge the chasm between the two encoders by creating a "correction notebook" for secondary-supervision.

Language Modelling Masked Language Modeling

CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing

no code implementations4 May 2023 Songyang Gao, Shihan Dou, Junjie Shan, Qi Zhang, Xuanjing Huang

Dataset bias, i. e., the over-reliance on dataset-specific literal heuristics, is getting increasing attention for its detrimental effect on the generalization ability of NLU models.

Causal Inference Disentanglement +1

Rumor Detection with Hierarchical Representation on Bipartite Adhoc Event Trees

no code implementations27 Apr 2023 Qi Zhang, Yayi Yang, Chongyang Shi, An Lao, Liang Hu, Shoujin Wang, Usman Naseem

Accordingly, we propose a novel rumor detection model with hierarchical representation on the bipartite adhoc event trees called BAET.

Inverting the Imaging Process by Learning an Implicit Camera Model

no code implementations CVPR 2023 Xin Huang, Qi Zhang, Ying Feng, Hongdong Li, Qing Wang

In principle, our new implicit neural camera model has the potential to benefit a wide array of other inverse imaging tasks.

NeAI: A Pre-convoluted Representation for Plug-and-Play Neural Ambient Illumination

no code implementations18 Apr 2023 Yiyu Zhuang, Qi Zhang, Xuan Wang, Hao Zhu, Ying Feng, Xiaoyu Li, Ying Shan, Xun Cao

Recent advances in implicit neural representation have demonstrated the ability to recover detailed geometry and material from multi-view images.

Disorder-invariant Implicit Neural Representation

no code implementations3 Apr 2023 Hao Zhu, Shaowen Xie, Zhen Liu, Fengyi Liu, Qi Zhang, You Zhou, Yi Lin, Zhan Ma, Xun Cao

However, the expressive power of INR is limited by the spectral bias in the network training.


A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models

no code implementations18 Mar 2023 Junjie Ye, Xuanting Chen, Nuo Xu, Can Zu, Zekai Shao, Shichun Liu, Yuhan Cui, Zeyang Zhou, Chao Gong, Yang shen, Jie zhou, Siming Chen, Tao Gui, Qi Zhang, Xuanjing Huang

GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on, have gained considerable attention due to their exceptional natural language processing capabilities.

Natural Language Understanding

IRGen: Generative Modeling for Image Retrieval

1 code implementation17 Mar 2023 Yidan Zhang, Ting Zhang, Dong Chen, Yujing Wang, Qi Chen, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Mao Yang, Qingmin Liao, Baining Guo

While generative modeling has been ubiquitous in natural language processing and computer vision, its application to image retrieval remains unexplored.

Image Retrieval Retrieval

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

1 code implementation15 Mar 2023 Daixuan Cheng, Shaohan Huang, Junyu Bi, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Furu Wei, Denvy Deng, Qi Zhang

Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generalization.

Prompt Engineering Retrieval

A Message Passing Perspective on Learning Dynamics of Contrastive Learning

1 code implementation8 Mar 2023 Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang

In recent years, contrastive learning achieves impressive results on self-supervised visual representation learning, but there still lacks a rigorous understanding of its learning dynamics.

Contrastive Learning Graph Attention +1

A Visual SLAM with Moving Object Trajectory Prediction

no code implementations3 Mar 2023 Qi Zhang, Siyuan Gou, Wenbin Li

Visual Simultaneous Localization and Mapping (SLAM) has received significant attention in recent years due to its ability to estimate camera trajectory and create an environment map using visual data alone, making a substantial contribution to autonomous driving applications, in particular, a real-world scenario with moving crowds and vehicles.

Autonomous Driving Simultaneous Localization and Mapping +1

How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks

no code implementations1 Mar 2023 Xuanting Chen, Junjie Ye, Can Zu, Nuo Xu, Rui Zheng, Minlong Peng, Jie zhou, Tao Gui, Qi Zhang, Xuanjing Huang

The GPT-3. 5 models have demonstrated impressive performance in various Natural Language Processing (NLP) tasks, showcasing their strong understanding and reasoning capabilities.

Natural Language Inference Natural Language Understanding +1

Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information

no code implementations19 Feb 2023 Zhen Guo, Qi Zhang, Xinwei An, Qisheng Zhang, Audun Jøsang, Lance M. Kaplan, Feng Chen, Dong H. Jeong, Jin-Hee Cho

Distinguishing the types of fake news spreaders based on their intent is critical because it will effectively guide how to intervene to mitigate the spread of fake news with different approaches.

Decision Making intent-classification +1

Enhancing Model Performance in Multilingual Information Retrieval with Comprehensive Data Engineering Techniques

no code implementations14 Feb 2023 Qi Zhang, Zijian Yang, Yilun Huang, Ze Chen, Zijian Cai, Kangxu Wang, Jiewen Zheng, Jiarong He, Jin Gao

In this paper, we present our solution to the Multilingual Information Retrieval Across a Continuum of Languages (MIRACL) challenge of WSDM CUP 2023\footnote{https://project-miracl. github. io/}.

Data Augmentation Information Retrieval +1

CCDN: Checkerboard Corner Detection Network for Robust Camera Calibration

no code implementations10 Feb 2023 Ben Chen, Caihua Xiong, Qi Zhang

Aiming to improve the checkerboard corner detection robustness against the images with poor quality, such as lens distortion, extreme poses, and noise, we propose a novel detection algorithm which can maintain high accuracy on inputs under multiply scenarios without any prior knowledge of the checkerboard pattern.

Camera Calibration

A Survey on Deep Learning based Time Series Analysis with Frequency Transformation

no code implementations4 Feb 2023 Kun Yi, Qi Zhang, Longbing Cao, Shoujin Wang, Guodong Long, Liang Hu, Hui He, Zhendong Niu, Wei Fan, Hui Xiong

Despite the growing attention and the proliferation of research in this emerging field, there is currently a lack of a systematic review and in-depth analysis of deep learning-based time series models with FT.

Time Series Time Series Analysis

Study of Optical Networks, 5G, Artificial Intelligence and Their Applications

no code implementations31 Jan 2023 Quanda Zhang, Qi Zhang

This paper discusses the application of artificial intelligence (AI) technology in optical communication networks and 5G.

PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks

no code implementations30 Jan 2023 Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

In this paper, we introduce PromptMix, a method for artificially boosting the size of existing datasets, that can be used to improve the performance of lightweight networks.

Crowd Counting Data Augmentation +2

DeciLS-PBO: an Effective Local Search Method for Pseudo-Boolean Optimization

no code implementations28 Jan 2023 Luyu Jiang, Dantong Ouyang, Qi Zhang, Liming Zhang

Local search is an effective method for solving large-scale combinatorial optimization problems, and it has made remarkable progress in recent years through several subtle mechanisms.

Combinatorial Optimization

Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective

no code implementations27 Jan 2023 Hui He, Qi Zhang, Shoujin Wang, Kun Yi, Zhendong Niu, Longbing Cao

To address this significant gap, we formulate the MTS fairness modeling problem as learning informative representations attending to both advantaged and disadvantaged variables.

Fairness Multivariate Time Series Forecasting +1

Wide-Angle Rectification via Content-Aware Conformal Mapping

no code implementations CVPR 2023 Qi Zhang, Hongdong Li, Qing Wang

Despite the proliferation of ultra wide-angle lenses on smartphone cameras, such lenses often come with severe image distortion (e. g. curved linear structure, unnaturally skewed faces).

Cross-Linguistic Syntactic Difference in Multilingual BERT: How Good is It and How Does It Affect Transfer?

1 code implementation21 Dec 2022 Ningyu Xu, Tao Gui, Ruotian Ma, Qi Zhang, Jingting Ye, Menghan Zhang, Xuanjing Huang

We demonstrate that the distance between the distributions of different languages is highly consistent with the syntactic difference in terms of linguistic formalisms.

Zero-Shot Cross-Lingual Transfer

SLAN: Self-Locator Aided Network for Cross-Modal Understanding

no code implementations28 Nov 2022 Jiang-Tian Zhai, Qi Zhang, Tong Wu, Xing-Yu Chen, Jiang-Jiang Liu, Bo Ren, Ming-Ming Cheng

By aggregating cross-modal information, the region filter selects key regions and the region adaptor updates their coordinates with text guidance.

Image Retrieval Retrieval

Fine-Grained Face Swapping via Regional GAN Inversion

no code implementations CVPR 2023 Zhian Liu, Maomao Li, Yong Zhang, Cairong Wang, Qi Zhang, Jue Wang, Yongwei Nie

We rethink face swapping from the perspective of fine-grained face editing, \textit{i. e., ``editing for swapping'' (E4S)}, and propose a framework that is based on the explicit disentanglement of the shape and texture of facial components.

Disentanglement Face Swapping

Attention-based Feature Compression for CNN Inference Offloading in Edge Computing

no code implementations24 Nov 2022 Nan Li, Alexandros Iosifidis, Qi Zhang

We design a feature compression module based on the channel attention method in CNN, to compress the intermediate data by selecting the most important features.

Edge-computing Feature Compression

Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications

no code implementations24 Nov 2022 Andrea Cavagna, Nan Li, Alexandros Iosifidis, Qi Zhang

The proposed Edge Intelligence framework consists of the proposed effectiveness encoding and effectiveness decoding.

Image Augmentation

Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing

no code implementations24 Nov 2022 Zhongtian Dong, Nan Li, Alexandros Iosifidis, Qi Zhang

It is shown that the model selection with distributed inference HALP can significantly improve service reliability compared to the conventional stand-alone computation.

Distributed Computing Edge-computing +2

Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields

no code implementations CVPR 2023 Yue Chen, Xingyu Chen, Xuan Wang, Qi Zhang, Yu Guo, Ying Shan, Fei Wang

Neural Radiance Fields (NeRF) have achieved photorealistic novel views synthesis; however, the requirement of accurate camera poses limits its application.

DINER: Disorder-Invariant Implicit Neural Representation

no code implementations CVPR 2023 Shaowen Xie, Hao Zhu, Zhen Liu, Qi Zhang, You Zhou, Xun Cao, Zhan Ma

Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problems.


Efficient Adversarial Training with Robust Early-Bird Tickets

1 code implementation14 Nov 2022 Zhiheng Xi, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang

Adversarial training is one of the most powerful methods to improve the robustness of pre-trained language models (PLMs).

Towards Understanding Omission in Dialogue Summarization

1 code implementation14 Nov 2022 Yicheng Zou, Kaitao Song, Xu Tan, Zhongkai Fu, Qi Zhang, Dongsheng Li, Tao Gui

By analyzing this dataset, we find that a large improvement in summarization quality can be achieved by providing ground-truth omission labels for the summarization model to recover omission information, which demonstrates the importance of omission detection for omission mitigation in dialogue summarization.

Perceptual Video Coding for Machines via Satisfied Machine Ratio Modeling

1 code implementation13 Nov 2022 Qi Zhang, Shanshe Wang, Xinfeng Zhang, Chuanmin Jia, Zhao Wang, Siwei Ma, Wen Gao

Furthermore, we introduce an auxiliary task to increase the prediction accuracy by predicting the SMR difference between two images in different quality levels.

Image Classification object-detection +3

Robust Lottery Tickets for Pre-trained Language Models

1 code implementation ACL 2022 Rui Zheng, Rong Bao, Yuhao Zhou, Di Liang, Sirui Wang, Wei Wu, Tao Gui, Qi Zhang, Xuanjing Huang

Recent works on Lottery Ticket Hypothesis have shown that pre-trained language models (PLMs) contain smaller matching subnetworks(winning tickets) which are capable of reaching accuracy comparable to the original models.

Adversarial Robustness

Line Spectral Estimation via Unlimited Sampling

no code implementations28 Oct 2022 Qi Zhang, Jiang Zhu, Zhiwei Xu, De Wen Soh

In addition, a two-stage US LSE (USLSE) is proposed where the line spectral signal is first recovered by iteratively executing DP and OMP, and then the parameters are estimated by applying a state-of-art LSE algorithm.

Efficient Learning of Decision-Making Models: A Penalty Block Coordinate Descent Algorithm for Data-Driven Inverse Optimization

no code implementations27 Oct 2022 Rishabh Gupta, Qi Zhang

In this work, we consider the inverse problem where we use prior decision data to uncover the underlying decision-making process in the form of a mathematical optimization model.

Decision Making

Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing

no code implementations24 Oct 2022 Nan Li, Alexandros Iosifidis, Qi Zhang

To solve the maximization problem, we propose a graph reinforcement learning-based early-exit mechanism (GRLE), which outperforms the state-of-the-art work, deep reinforcement learning-based online offloading (DROO) and its enhanced method, DROO with early-exit mechanism (DROOE), under different dynamic scenarios.

Decision Making Edge-computing +2

How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders

1 code implementation15 Oct 2022 Qi Zhang, Yifei Wang, Yisen Wang

Masked Autoencoders (MAE) based on a reconstruction task have risen to be a promising paradigm for self-supervised learning (SSL) and achieve state-of-the-art performance across different benchmark datasets.

Contrastive Learning Self-Supervised Learning

Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding

1 code implementation14 Oct 2022 Songyang Gao, Shihan Dou, Qi Zhang, Xuanjing Huang

Dataset bias has attracted increasing attention recently for its detrimental effect on the generalization ability of fine-tuned models.

Sentence Embedding Sentence-Embedding

Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER

no code implementations10 Oct 2022 Ruotian Ma, Xuanting Chen, Lin Zhang, Xin Zhou, Junzhe Wang, Tao Gui, Qi Zhang, Xiang Gao, Yunwen Chen

In this work, we conduct an empirical study on the "Unlabeled Entity Problem" and find that it leads to severe confusion between "O" and entities, decreasing class discrimination of old classes and declining the model's ability to learn new classes.

class-incremental learning Class Incremental Learning +4

Edge-Varying Fourier Graph Networks for Multivariate Time Series Forecasting

no code implementations6 Oct 2022 Kun Yi, Qi Zhang, Liang Hu, Hui He, Ning An, Longbing Cao, Zhendong Niu

The key problem in multivariate time series (MTS) analysis and forecasting aims to disclose the underlying couplings between variables that drive the co-movements.

Multivariate Time Series Forecasting Time Series

Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models

1 code implementation27 Sep 2022 Xiuying Wei, Yunchen Zhang, Xiangguo Zhang, Ruihao Gong, Shanghang Zhang, Qi Zhang, Fengwei Yu, Xianglong Liu

With the trends of large NLP models, the increasing memory and computation costs hinder their efficient deployment on resource-limited devices.


Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering

1 code implementation COLING 2022 Siyuan Wang, Zhongyu Wei, Zhihao Fan, Qi Zhang, Xuanjing Huang

In this paper, we propose an interpretable stepwise reasoning framework to incorporate both single-hop supporting sentence identification and single-hop question generation at each intermediate step, and utilize the inference of the current hop for the next until reasoning out the final result.

Multi-hop Question Answering Question Answering +2

Causal Intervention Improves Implicit Sentiment Analysis

no code implementations COLING 2022 Siyin Wang, Jie zhou, Changzhi Sun, Junjie Ye, Tao Gui, Qi Zhang, Xuanjing Huang

In this work, we propose a causal intervention model for Implicit Sentiment Analysis using Instrumental Variable (ISAIV).

Sentiment Analysis

Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training

no code implementations15 Aug 2022 Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

JPEG image compression algorithm is a widely used technique for image size reduction in edge and cloud computing settings.

Cloud Computing Crowd Counting +1

Exploring Anchor-based Detection for Ego4D Natural Language Query

no code implementations10 Aug 2022 Sipeng Zheng, Qi Zhang, Bei Liu, Qin Jin, Jianlong Fu

In this paper we provide the technique report of Ego4D natural language query challenge in CVPR 2022.

Video Understanding

A Semantic Alignment System for Multilingual Query-Product Retrieval

no code implementations5 Aug 2022 Qi Zhang, Zijian Yang, Yilun Huang, Ze Chen, Zijian Cai, Kangxu Wang, Jiewen Zheng, Jiarong He, Jin Gao

Our models are all trained with cross-entropy loss to classify the query-product pairs into ESCI 4 categories at first, and then we use weighted sum with the 4-class probabilities to get the score for ranking.

Data Augmentation Retrieval

Efficient High-Resolution Deep Learning: A Survey

no code implementations26 Jul 2022 Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

Cameras in modern devices such as smartphones, satellites and medical equipment are capable of capturing very high resolution images and videos.

Vocal Bursts Intensity Prediction

PanGu-Coder: Program Synthesis with Function-Level Language Modeling

1 code implementation22 Jul 2022 Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, Guchun Zhang, Yinpeng Guo, Zhongqi Li, Qi Zhang, Meng Xiao, Bo Shen, Lin Li, Hao Yu, Li Yan, Pingyi Zhou, Xin Wang, Yuchi Ma, Ignacio Iacobacci, Yasheng Wang, Guangtai Liang, Jiansheng Wei, Xin Jiang, Qianxiang Wang, Qun Liu

We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i. e. the synthesis of programming language solutions given a natural language problem description.

Code Generation Language Modelling +2

Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing

no code implementations22 Jul 2022 Nan Li, Alexandros Iosifidis, Qi Zhang

To reduce the computation time and communication overhead, we propose a novel collaborative edge computing using fused-layer parallelization to partition a CNN model into multiple blocks of convolutional layers.


Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing

no code implementations22 Jul 2022 Nan Li, Alexandros Iosifidis, Qi Zhang

This paper studies inference acceleration using distributed convolutional neural networks (CNNs) in collaborative edge computing.


Unifying Event Detection and Captioning as Sequence Generation via Pre-Training

1 code implementation18 Jul 2022 Qi Zhang, Yuqing Song, Qin Jin

Dense video captioning aims to generate corresponding text descriptions for a series of events in the untrimmed video, which can be divided into two sub-tasks, event detection and event captioning.

Dense Video Captioning Event Detection

Neural Color Operators for Sequential Image Retouching

2 code implementations17 Jul 2022 Yili Wang, Xin Li, Kun Xu, Dongliang He, Qi Zhang, Fu Li, Errui Ding

The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar.

Image Enhancement Image Retouching

Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution Regression

1 code implementation11 Jul 2022 Qi Zhang, Bing Li, Lingzhou Xue

We introduce a new approach to nonlinear sufficient dimension reduction in cases where both the predictor and the response are distributional data, modeled as members of a metric space.

Dimensionality Reduction regression

Neural Parameterization for Dynamic Human Head Editing

no code implementations1 Jul 2022 Li Ma, Xiaoyu Li, Jing Liao, Xuan Wang, Qi Zhang, Jue Wang, Pedro Sander

Implicit radiance functions emerged as a powerful scene representation for reconstructing and rendering photo-realistic views of a 3D scene.

Supervised Deep Hashing for High-dimensional and Heterogeneous Case-based Reasoning

no code implementations29 Jun 2022 Qi Zhang, Liang Hu, Chongyang Shi, Ke Liu, Longbing Cao

Case-based Reasoning (CBR) on high-dimensional and heterogeneous data is a trending yet challenging and computationally expensive task in the real world.

Incremental Learning Quantization +2

Convergence and Price of Anarchy Guarantees of the Softmax Policy Gradient in Markov Potential Games

no code implementations15 Jun 2022 Dingyang Chen, Qi Zhang, Thinh T. Doan

Our focus in this paper is to study the convergence of the policy gradient method for solving MPGs under softmax policy parameterization, both tabular and parameterized with general function approximators such as neural networks.

Policy Gradient Methods

A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning

no code implementations12 Jun 2022 Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M. Kaplan, Dong H. Jeong, Audun Jøsang

We found that only a few studies have leveraged the mature uncertainty research in belief/evidence theories in ML/DL to tackle complex problems under different types of uncertainty.

Decision Making

A Neural Corpus Indexer for Document Retrieval

1 code implementation6 Jun 2022 Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Allen Sun, Weiwei Deng, Qi Zhang, Mao Yang

To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.

Retrieval TriviaQA

A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis

no code implementations31 May 2022 Qi Zhang, Jie zhou, Qin Chen, Qingchun Bai, Jun Xiao, Liang He

Notably, we propose a Knowledge-Enhanced Adversarial Model (\texttt{KEAM}) with both implicit distributed and explicit structural knowledge to enhance the cross-lingual transfer.

Cross-Lingual Transfer Sentiment Analysis

Enhancing Event-Level Sentiment Analysis with Structured Arguments

1 code implementation31 May 2022 Qi Zhang, Jie zhou, Qin Chen, Qinchun Bai, Liang He

Previous studies about event-level sentiment analysis (SA) usually model the event as a topic, a category or target terms, while the structured arguments (e. g., subject, object, time and location) that have potential effects on the sentiment are not well studied.

Event Extraction Sentiment Analysis

Dynamic Split Computing for Efficient Deep Edge Intelligence

no code implementations23 May 2022 Arian Bakhtiarnia, Nemanja Milošević, Qi Zhang, Dragana Bajović, Alexandros Iosifidis

Split computing is a paradigm where a DNN is split into two sections; the first section is executed on the end device, and the output is transmitted to the edge server where the final section is executed.

Edge-computing Hyperparameter Optimization

Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities

no code implementations22 May 2022 Shoujin Wang, Qi Zhang, Liang Hu, Xiuzhen Zhang, Yan Wang, Charu Aggarwal

In recent years, sequential recommender systems (SRSs) and session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs to capture users' short-term but dynamic preferences for enabling more timely and accurate recommendations.

Session-Based Recommendations

Cross-View Cross-Scene Multi-View Crowd Counting

no code implementations CVPR 2021 Qi Zhang, Wei Lin, Antoni B. Chan

Multi-view crowd counting has been previously proposed to utilize multi-cameras to extend the field-of-view of a single camera, capturing more people in the scene, and improve counting performance for occluded people or those in low resolution.

Camera Calibration Crowd Counting

Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array

no code implementations27 Apr 2022 Xichao Zhan, YiWen Chen, Feng Shu, Xin Cheng, Yuanyuan Wu, Qi Zhang, Yifang Li, Peng Zhang

In the proposed Max-RP-QI, a quadratic interpolation scheme is adopted to interpolate the three DOA values corresponding to the largest three receive powers of Max-RP.

Process Knowledge-infused Learning for Suicidality Assessment on Social Media

no code implementations26 Apr 2022 Kaushik Roy, Manas Gaur, Qi Zhang, Amit Sheth

Improving the performance and natural language explanations of deep learning algorithms is a priority for adoption by humans in the real world.

Explainable Artificial Intelligence (XAI)

Multi-view Information Bottleneck Without Variational Approximation

1 code implementation22 Apr 2022 Qi Zhang, Shujian Yu, Jingmin Xin, Badong Chen

By "intelligently" fusing the complementary information across different views, multi-view learning is able to improve the performance of classification tasks.


A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets

1 code implementation19 Apr 2022 Wei Chen, Zhiwei Li, Hongyi Fang, Qianyuan Yao, Cheng Zhong, Jianye Hao, Qi Zhang, Xuanjing Huang, Jiajie Peng, Zhongyu Wei

In recent years, interest has arisen in using machine learning to improve the efficiency of automatic medical consultation and enhance patient experience.

Dialogue Act Classification Dialogue Understanding +4

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

1 code implementation2 Apr 2022 Jing He, Yiyi Zhou, Qi Zhang, Jun Peng, Yunhang Shen, Xiaoshuai Sun, Chao Chen, Rongrong Ji

Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation.

Image Generation regression

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis

no code implementations30 Mar 2022 Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang

To this end, we propose a cross-metric multi-dimensional root cause analysis method, named CMMD, which consists of two key components: 1) relationship modeling, which utilizes graph neural network (GNN) to model the unknown complex calculation among metrics and aggregation function among dimensions from historical data; 2) root cause localization, which adopts the genetic algorithm to efficiently and effectively dive into the raw data and localize the abnormal dimension(s) once the KPI anomalies are detected.

UV Volumes for Real-time Rendering of Editable Free-view Human Performance

1 code implementation CVPR 2023 Yue Chen, Xuan Wang, Xingyu Chen, Qi Zhang, Xiaoyu Li, Yu Guo, Jue Wang, Fei Wang

Neural volume rendering enables photo-realistic renderings of a human performer in free-view, a critical task in immersive VR/AR applications.

Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap

1 code implementation25 Mar 2022 Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

Our theory suggests an alternative understanding of contrastive learning: the role of aligning positive samples is more like a surrogate task than an ultimate goal, and the overlapped augmented views (i. e., the chaos) create a ladder for contrastive learning to gradually learn class-separated representations.

Contrastive Learning Model Selection +1

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation

no code implementations23 Mar 2022 Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He

Specifically, PEAR not only captures feature-level and item-level interactions, but also models item contexts from both the initial ranking list and the historical clicked item list.

Recommendation Systems Re-Ranking

Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents

1 code implementation Findings (ACL) 2022 Yicheng Zou, Hongwei Liu, Tao Gui, Junzhe Wang, Qi Zhang, Meng Tang, Haixiang Li, Daniel Wang

Text semantic matching is a fundamental task that has been widely used in various scenarios, such as community question answering, information retrieval, and recommendation.

Community Question Answering Information Retrieval +1

An Effective Way for Cross-Market Recommendation with Hybrid Pre-Ranking and Ranking Models

1 code implementation2 Mar 2022 Qi Zhang, Zijian Yang, Yilun Huang, Jiarong He, Lixiang Wang

The Cross-Market Recommendation task of WSDM CUP 2022 is about finding solutions to improve individual recommendation systems in resource-scarce target markets by leveraging data from similar high-resource source markets.

feature selection Recommendation Systems

Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games

no code implementations ICLR 2022 Dingyang Chen, Yile Li, Qi Zhang

Recent success in cooperative multi-agent reinforcement learning (MARL) relies on centralized training and policy sharing.

Multi-agent Reinforcement Learning

HousE: Knowledge Graph Embedding with Householder Parameterization

1 code implementation16 Feb 2022 Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties.

Knowledge Graph Embedding Relation Mapping

Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective

2 code implementations COLING 2022 Shihan Dou, Rui Zheng, Ting Wu, Songyang Gao, Junjie Shan, Qi Zhang, Yueming Wu, Xuanjing Huang

Most of the existing debiasing methods often identify and weaken these samples with biased features (i. e., superficial surface features that cause such spurious correlations).

Fact Verification Natural Language Inference +1

Post-Training Quantization for Cross-Platform Learned Image Compression

no code implementations15 Feb 2022 Dailan He, Ziming Yang, Yuan Chen, Qi Zhang, Hongwei Qin, Yan Wang

It has been witnessed that learned image compression has outperformed conventional image coding techniques and tends to be practical in industrial applications.

Image Compression Quantization

Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval

2 code implementations14 Jan 2022 Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Yingxia Shao, Defu Lian, Chaozhuo Li, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang, Xing Xie

In this work, we tackle this problem with Bi-Granular Document Representation, where the lightweight sparse embeddings are indexed and standby in memory for coarse-grained candidate search, and the heavyweight dense embeddings are hosted in disk for fine-grained post verification.

Quantization Retrieval

A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning

no code implementations9 Jan 2022 Sai Qian Zhang, Jieyu Lin, Qi Zhang

Federated learning (FL) is a training technique that enables client devices to jointly learn a shared model by aggregating locally-computed models without exposing their raw data.

Federated Learning Multi-agent Reinforcement Learning +2

Hallucinated Neural Radiance Fields in the Wild

no code implementations CVPR 2022 Xingyu Chen, Qi Zhang, Xiaoyu Li, Yue Chen, Ying Feng, Xuan Wang, Jue Wang

This paper studies the problem of hallucinated NeRF: i. e., recovering a realistic NeRF at a different time of day from a group of tourism images.

Novel View Synthesis

HDR-NeRF: High Dynamic Range Neural Radiance Fields

no code implementations CVPR 2022 Xin Huang, Qi Zhang, Ying Feng, Hongdong Li, Xuan Wang, Qing Wang

The key to our method is to model the physical imaging process, which dictates that the radiance of a scene point transforms to a pixel value in the LDR image with two implicit functions: a radiance field and a tone mapper.

Vocal Bursts Intensity Prediction

Deblur-NeRF: Neural Radiance Fields from Blurry Images

no code implementations CVPR 2022 Li Ma, Xiaoyu Li, Jing Liao, Qi Zhang, Xuan Wang, Jue Wang, Pedro V. Sander

We demonstrate that our method can be used on both camera motion blur and defocus blur: the two most common types of blur in real scenes.

3D Scene Reconstruction Novel View Synthesis

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

1 code implementation5 Nov 2021 Yuhang Li, Mingzhu Shen, Jian Ma, Yan Ren, Mingxin Zhao, Qi Zhang, Ruihao Gong, Fengwei Yu, Junjie Yan

Surprisingly, no existing algorithm wins every challenge in MQBench, and we hope this work could inspire future research directions.