Search Results for author: Ming Zhang

Found 127 papers, 43 papers with code

Partial FC: Training 10 Million Identities on a Single Machine

7 code implementations11 Oct 2020 Xiang An, Xuhan Zhu, Yang Xiao, Lan Wu, Ming Zhang, Yuan Gao, Bin Qin, Debing Zhang, Ying Fu

The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.

Face Identification Face Recognition +2

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

14 code implementations29 Oct 2018 Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang

Afterwards, a multi-head self-attentive neural network with residual connections is proposed to explicitly model the feature interactions in the low-dimensional space.

Click-Through Rate Prediction Recommendation Systems

LINE: Large-scale Information Network Embedding

8 code implementations12 Mar 2015 Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei

This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.

Graph Embedding Link Prediction +2

Session-based Social Recommendation via Dynamic Graph Attention Networks

2 code implementations25 Feb 2019 Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang

However, recommendation in online communities is a challenging problem: 1) users' interests are dynamic, and 2) users are influenced by their friends.

 Ranked #1 on Recommendation Systems on Douban (NDCG metric)

Graph Attention Recommendation Systems

Ekar: An Explainable Method for Knowledge Aware Recommendation

2 code implementations22 Jun 2019 Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang

Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.

Knowledge-Aware Recommendation Knowledge Graphs +1

Visualizing Large-scale and High-dimensional Data

5 code implementations1 Feb 2016 Jian Tang, Jingzhou Liu, Ming Zhang, Qiaozhu Mei

We propose the LargeVis, a technique that first constructs an accurately approximated K-nearest neighbor graph from the data and then layouts the graph in the low-dimensional space.

graph construction Vocal Bursts Intensity Prediction

EasyQuant: Post-training Quantization via Scale Optimization

1 code implementation30 Jun 2020 Di Wu, Qi Tang, Yongle Zhao, Ming Zhang, Ying Fu, Debing Zhang

The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications.

Quantization

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs

2 code implementations NeurIPS 2023 Zhaocheng Zhu, Xinyu Yuan, Mikhail Galkin, Sophie Xhonneux, Ming Zhang, Maxime Gazeau, Jian Tang

Experiments on both transductive and inductive knowledge graph reasoning benchmarks show that A*Net achieves competitive performance with existing state-of-the-art path-based methods, while merely visiting 10% nodes and 10% edges at each iteration.

Knowledge Graphs

RJUA-QA: A Comprehensive QA Dataset for Urology

1 code implementation15 Dec 2023 Shiwei Lyu, Chenfei Chi, Hongbo Cai, Lei Shi, Xiaoyan Yang, Lei Liu, Xiang Chen, Deng Zhao, Zhiqiang Zhang, Xianguo Lyu, Ming Zhang, Fangzhou Li, Xiaowei Ma, Yue Shen, Jinjie Gu, Wei Xue, Yiran Huang

We introduce RJUA-QA, a novel medical dataset for question answering (QA) and reasoning with clinical evidence, contributing to bridge the gap between general large language models (LLMs) and medical-specific LLM applications.

Question Answering

Multi-agent Trajectory Prediction with Fuzzy Query Attention

1 code implementation NeurIPS 2020 Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu

Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.

Decision Making Traffic Prediction +1

Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction

1 code implementation13 Mar 2018 Lu-chen Liu, Jianhao Shen, Ming Zhang, Zichang Wang, Jian Tang

One important application is clinical endpoint prediction, which aims to predict whether a disease, a symptom or an abnormal lab test will happen in the future according to patients' history records.

Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks

1 code implementation ACL 2020 Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang

Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems.

Dialogue Generation Language Modelling +1

Neural Correction Model for Open-Domain Named Entity Recognition

1 code implementation13 Sep 2019 Mengdi Zhu, Zheye Deng, Wenhan Xiong, Mo Yu, Ming Zhang, William Yang Wang

In this work, to address the low precision and recall problems, we first utilize DBpedia as the source of distant supervision to annotate abstracts from Wikipedia and design a neural correction model trained with a human-annotated NER dataset, DocRED, to correct the false entity labels.

Multi-Task Learning named-entity-recognition +4

An Attention-based Collaboration Framework for Multi-View Network Representation Learning

1 code implementation19 Sep 2017 Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han

Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network.

Representation Learning

Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems

2 code implementations23 Oct 2016 Yiping Song, Rui Yan, Xiang Li, Dongyan Zhao, Ming Zhang

In this paper, we propose a novel ensemble of retrieval-based and generation-based dialog systems in the open domain.

Retrieval

FIMO: A Challenge Formal Dataset for Automated Theorem Proving

1 code implementation8 Sep 2023 Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu

We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems.

Automated Theorem Proving

Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration

1 code implementation5 Jun 2020 Ming Zhang, Yawei Wang, Xiaoteng Ma, Li Xia, Jun Yang, Zhiheng Li, Xiu Li

The generative adversarial imitation learning (GAIL) has provided an adversarial learning framework for imitating expert policy from demonstrations in high-dimensional continuous tasks.

Continuous Control Imitation Learning

Kernel-based Substructure Exploration for Next POI Recommendation

1 code implementation8 Oct 2022 Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang

To tackle the above issues, we propose a Kernel-Based Graph Neural Network (KBGNN) for next POI recommendation, which combines the characteristics of both geographical and sequential influences in a collaborative way.

Recommendation Systems

Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data

1 code implementation29 Mar 2023 Bin Feng, Tenglong Ao, Zequn Liu, Wei Ju, Libin Liu, Ming Zhang

How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task.

Disentanglement

End-to-End Rubbing Restoration Using Generative Adversarial Networks

1 code implementation8 May 2022 Gongbo Sun, Zijie Zheng, Ming Zhang

Specifically, we collect characters from the Zhang Menglong Bei and build up the first rubbing restoration dataset.

Generative Adversarial Network

A Diffusion model for POI recommendation

1 code implementation14 Apr 2023 Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang

In this paper, we propose Diff-POI: a Diffusion-based model that samples the user's spatial preference for the next POI recommendation.

Redundancy-Free Self-Supervised Relational Learning for Graph Clustering

1 code implementation9 Sep 2023 Si-Yu Yi, Wei Ju, Yifang Qin, Xiao Luo, Luchen Liu, Yong-Dao Zhou, Ming Zhang

Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks in recent years.

Attribute Clustering +4

MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping

1 code implementation21 Jan 2021 Ruimin Feng, Jiayi Zhao, He Wang, Baofeng Yang, Jie Feng, Yuting Shi, Ming Zhang, Chunlei Liu, Yuyao Zhang, Jie Zhuang, Hongjiang Wei

However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label.

SSIM

Orthonormal Product Quantization Network for Scalable Face Image Retrieval

1 code implementation1 Jul 2021 Ming Zhang, Xuefei Zhe, Hong Yan

Experiments are conducted on four commonly-used face datasets under both seen and unseen identities retrieval settings.

Deep Hashing Face Image Retrieval +2

Context-aware Natural Language Generation with Recurrent Neural Networks

1 code implementation29 Nov 2016 Jian Tang, Yifan Yang, Sam Carton, Ming Zhang, Qiaozhu Mei

This paper studied generating natural languages at particular contexts or situations.

Text Generation

DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

1 code implementation21 Jun 2021 Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang

In this paper, we propose a novel disentangled heterogeneous graph attention network DisenHAN for top-$N$ recommendation, which learns disentangled user/item representations from different aspects in a heterogeneous information network.

Collaborative Filtering Graph Attention +1

Preparing Lessons for Progressive Training on Language Models

1 code implementation17 Jan 2024 Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, Qun Liu

The rapid progress of Transformers in artificial intelligence has come at the cost of increased resource consumption and greenhouse gas emissions due to growing model sizes.

Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation

1 code implementation Findings (NAACL) 2022 Junwei Yang, Zequn Liu, Ming Zhang, Sheng Wang

Collectively, we envision our method will become an important benchmark for evaluating Graph2Text methods and advance biomedical research for complex diseases.

named-entity-recognition Named Entity Recognition +2

GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow

1 code implementation23 Feb 2023 Fang Sun, Zhihao Zhan, Hongyu Guo, Ming Zhang, Jian Tang

In particular, GraphVF represents the first controllable geometry-aware, protein-specific molecule generation method, which can generate binding 3D molecules with tailored sub-structures and physio-chemical properties.

3D Molecule Generation Drug Discovery

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

1 code implementation25 May 2021 Xiao Luo, Daqing Wu, Yiyang Gu, Chong Chen, Luchen Liu, Jinwen Ma, Ming Zhang, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua

Besides, CHCF integrates criterion learning and user preference learning into a unified framework, which can be trained jointly for the interaction prediction of the target behavior.

Collaborative Filtering Metric Learning +1

Towards Automated ICD Coding Using Deep Learning

no code implementations11 Nov 2017 Haoran Shi, Pengtao Xie, Zhiting Hu, Ming Zhang, Eric P. Xing

Considering the complicated and dedicated process to assign correct codes to each patient admission based on overall diagnosis, we propose a hierarchical deep learning model with attention mechanism which can automatically assign ICD diagnostic codes given written diagnosis.

General Classification Management

Syntax Aware LSTM Model for Chinese Semantic Role Labeling

no code implementations3 Apr 2017 Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang

As for semantic role labeling (SRL) task, when it comes to utilizing parsing information, both traditional methods and recent recurrent neural network (RNN) based methods use the feature engineering way.

Chinese Semantic Role Labeling Dependency Parsing +2

Two-Bit Networks for Deep Learning on Resource-Constrained Embedded Devices

no code implementations2 Jan 2017 Wenjia Meng, Zonghua Gu, Ming Zhang, Zhaohui Wu

With the rapid proliferation of Internet of Things and intelligent edge devices, there is an increasing need for implementing machine learning algorithms, including deep learning, on resource-constrained mobile embedded devices with limited memory and computation power.

Computational Efficiency General Classification +2

Less is More: Learning Prominent and Diverse Topics for Data Summarization

no code implementations29 Nov 2016 Jian Tang, Cheng Li, Ming Zhang, Qiaozhu Mei

With this reinforced random walk as a general process embedded in classical topic models, we obtain \textit{diverse topic models} that are able to extract the most prominent and diverse topics from data.

Data Summarization Topic Models

Improving Color Constancy by Discounting the Variation of Camera Spectral Sensitivity

no code implementations6 Sep 2016 Shao-Bing Gao, Ming Zhang, Chao-Yi Li, Yong-Jie Li

Most color constancy (CC) models have been designed to first estimate the illuminant color, which is then removed from the color biased image to obtain an image taken under white light, without the explicit consideration of CSS effect on CC.

Color Constancy

Dialogue Session Segmentation by Embedding-Enhanced TextTiling

no code implementations13 Oct 2016 Yiping Song, Lili Mou, Rui Yan, Li Yi, Zinan Zhu, Xiaohua Hu, Ming Zhang

In human-computer conversation systems, the context of a user-issued utterance is particularly important because it provides useful background information of the conversation.

Word Embeddings

World Knowledge as Indirect Supervision for Document Clustering

no code implementations30 Jul 2016 Chenguang Wang, Yangqiu Song, Dan Roth, Ming Zhang, Jiawei Han

We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network.

Clustering World Knowledge

Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction

no code implementations25 May 2016 Yichun Yin, Furu Wei, Li Dong, Kaimeng Xu, Ming Zhang, Ming Zhou

In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths.

Term Extraction

StalemateBreaker: A Proactive Content-Introducing Approach to Automatic Human-Computer Conversation

no code implementations15 Apr 2016 Xiang Li, Lili Mou, Rui Yan, Ming Zhang

In this paper, we propose StalemateBreaker, a conversation system that can proactively introduce new content when appropriate.

"Look Ma, No Hands!" A Parameter-Free Topic Model

no code implementations10 Sep 2014 Jian Tang, Ming Zhang, Qiaozhu Mei

We show that the new parameter can be further eliminated by two parameter-free treatments: either by monitoring the diversity among the discovered topics or by a weak supervision from users in the form of an exemplar topic.

Model Selection Topic Models

Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control

no code implementations3 Oct 2018 Wendi Xu, Ming Zhang

Despite its remarkable empirical success as a highly competitive branch of artificial intelligence, deep learning is often blamed for its widely known low interpretation and lack of firm and rigorous mathematical foundation.

Image Super-Resolution

Towards WARSHIP: Combining Components of Brain-Inspired Computing of RSH for Image Super Resolution

no code implementations3 Oct 2018 Wendi Xu, Ming Zhang

Evolution of deep learning shows that some algorithmic tricks are more durable , while others are not.

Image Super-Resolution

Efficient Spiking Neural Networks with Logarithmic Temporal Coding

no code implementations10 Nov 2018 Ming Zhang, Nenggan Zheng, De Ma, Gang Pan, Zonghua Gu

A Spiking Neural Network (SNN) can be trained indirectly by first training an Artificial Neural Network (ANN) with the conventional backpropagation algorithm, then converting it into an SNN.

Syntax Aware LSTM model for Semantic Role Labeling

no code implementations WS 2017 Feng Qian, Lei Sha, Baobao Chang, Lu-chen Liu, Ming Zhang

In Semantic Role Labeling (SRL) task, the tree structured dependency relation is rich in syntax information, but it is not well handled by existing models.

Feature Engineering Machine Translation +4

Diversifying Neural Conversation Model with Maximal Marginal Relevance

no code implementations IJCNLP 2017 Yiping Song, Zhiliang Tian, Dongyan Zhao, Ming Zhang, Rui Yan

However, traditional seq2seq suffer from a severe weakness: during beam search decoding, they tend to rank universal replies at the top of the candidate list, resulting in the lack of diversity among candidate replies.

Document Summarization Information Retrieval +1

Combating Fake News: A Survey on Identification and Mitigation Techniques

no code implementations18 Jan 2019 Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu

The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion.

Misinformation

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction

no code implementations20 Mar 2019 Lu-chen Liu, Haoran Li, Zhiting Hu, Haoran Shi, Zichang Wang, Jian Tang, Ming Zhang

Our model learns hierarchical representationsof event sequences, to adaptively distinguish between short-range and long-range events, and accurately capture coretemporal dependencies.

Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation

no code implementations14 Oct 2019 Lu-chen Liu, Haoxian Wu, Zichang Wang, Zequn Liu, Ming Zhang

Rather than directly applying the LSTM model to the event sequences, our proposed model firstly aggregates heterogeneous clinical events in a short period and then captures temporal interactions of the aggregated representations with LSTM.

PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction

no code implementations COLING 2020 Yichun Yin, Chenguang Wang, Ming Zhang

Dependency context-based word embedding jointly learns the representations of word and dependency context, and has been proved effective in aspect term extraction.

Aspect Term Extraction and Sentiment Classification POS +2

Predictive Multi-level Patient Representations from Electronic Health Records

no code implementations12 Nov 2019 Zichang Wang, Haoran Li, Lu-chen Liu, Haoxian Wu, Ming Zhang

Most related studies transform EHR data of a patient into a sequence of clinical events in temporal order and then use sequential models to learn patient representations for outcome prediction.

Learning to Answer Ambiguous Questions with Knowledge Graph

no code implementations25 Dec 2019 Yikai Zhu, Jianhao Shen, Ming Zhang

In the task of factoid question answering over knowledge base, many questions have more than one plausible interpretation.

Question Answering

When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications

no code implementations24 May 2020 Zequn Liu, Ruiyi Zhang, Yiping Song, Ming Zhang

Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low-resource language generation.

Few-Shot Text Classification Language Modelling +3

Augmented Bi-path Network for Few-shot Learning

no code implementations15 Jul 2020 Baoming Yan, Chen Zhou, Bo Zhao, Kan Guo, Jiang Yang, Xiaobo Li, Ming Zhang, Yizhou Wang

Finally, the model learns to compare global and local features separately, i. e., in two paths, before merging the similarities.

Few-Shot Learning

MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion

no code implementations23 Sep 2020 Zehan Zhang, Ming Zhang, Zhidong Liang, Xian Zhao, Ming Yang, Wenming Tan, ShiLiang Pu

Experimental results on the KITTI dataset demonstrate significant improvement in filtering false positive over the approach using only point cloud data.

Autonomous Driving

Fast MNAS: Uncertainty-aware Neural Architecture Search with Lifelong Learning

no code implementations1 Jan 2021 Jihao Liu, Yangting Sun, Ming Zhang, Boxiao Liu, Yu Liu

Further, a life-long knowledge pool together with a block similarity function is proposed to utilize the lifelong parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search

Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation

no code implementations9 Oct 2020 Yicheng Wu, Chengwei Pan, Shuqi Wang, Ming Zhang, Yong Xia, Yizhou Yu

Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases.

Snowmass 2021 LoI: Determination of cosmic ray properties in the local interstellar medium with all-sky anisotropy observations

no code implementations10 Sep 2020 Paolo Desiati, Juan Carlos Díaz Vélez, Nikolai Pogorelov, Ming Zhang

Propagation of Galactic cosmic rays (CR) in the interstellar medium (ISM) is among the unsolved problems in particle astrophysics.

High Energy Astrophysical Phenomena

New gedanken experiment on higher-dimensional asymptotically AdS Reissner-Nordström black hole

no code implementations16 Sep 2020 Ming Zhang, Jie Jiang

Viewing the negative cosmological constant as a dynamical quantity derived from the matter field, we study the weak cosmic censorship conjecture for the higher-dimensional asymptotically AdS Reissner-Nordstr\"om black hole.

General Relativity and Quantum Cosmology High Energy Physics - Theory

$K$-theoretic quasimap wall-crossing

no code implementations2 Dec 2020 Ming Zhang, Yang Zhou

In this paper, we prove a K-theoretic wall-crossing formula for $\epsilon$-stable quasimaps for all GIT targets in all genera.

Algebraic Geometry Mathematical Physics Mathematical Physics 14N35

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

no code implementations14 Dec 2020 Jiafa He, Chengwei Pan, Can Yang, Ming Zhang, Yang Wang, Xiaowei Zhou, Yizhou Yu

The main idea is to use CNNs to learn local appearances of vessels in image crops while using another point-cloud network to learn the global geometry of vessels in the entire image.

Representation Learning

Tomographic imaging of complete quantum state of matter by ultrafast diffraction

no code implementations22 Dec 2020 Ming Zhang, Shuqiao Zhang, Haitan Xu, Hankai Zhang, Xiangxu Mu, R. J. Dwayne Miller, Anatoly Ischenko, Oriol Vendrell, Zheng Li

With the ability to directly obtain the Wigner function and density matrix of photon states, quantum tomography (QT) has had a significant impact on quantum optics, quantum computing and quantum information.

Quantum Physics

$P-V$ criticality and Joule-Thomson Expansion of Hayward-AdS black holes in 4D Einstein-Gauss-Bonnet gravity

no code implementations8 Feb 2021 Ming Zhang, Chao-Ming Zhang, De-Cheng Zou, Rui-Hong Yue

In this paper, the $P-V$ criticality and Joule-Thomson Expansion of Hayward-AdS black holes in 4D Einstein-Gauss-Bonnet gravity are studied in the extended phase space.

Action Detection High Energy Physics - Theory

Topologically protected valley-dependent quantum photonic circuits

no code implementations11 Mar 2021 Yang Chen, Xin-Tao He, Yu-Jie Cheng, Hao-Yang Qiu, Lan-Tian Feng, Ming Zhang, Dao-Xin Dai, Guang-Can Guo, Jian-Wen Dong, Xi-Feng Ren

Topological photonics has been introduced as a powerful platform for integrated optics, since it can deal with robust light transport, and be further extended to the quantum world.

Quantum Physics Optics

Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval

no code implementations17 Mar 2021 Ming Zhang, Hong Yan

Recently, deep classwise hashing introduced a classwise loss supervised by class labels information alternatively; however, we find it still has its drawback.

Image Retrieval Retrieval

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

no code implementations26 Mar 2021 Ming Zhang, Mingming Zhang, Yiming Chen, Mingyang Li

In this work, we propose a novel method for performing inertial aided navigation, by using deep neural networks (DNNs).

Sensor Fusion

Time-dependent Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective

no code implementations2 Mar 2021 Junjun Mao, Xiaoyan Qiu, Weiwei Qin, Luyang Xu, Ming Zhang, Mingkang Zhong

The CL/F of the non-CGC haplotype carrier was 14. 4% lower than that of the CGC haplotype carrier at 3 months post operation.

FNAS: Uncertainty-Aware Fast Neural Architecture Search

no code implementations25 May 2021 Jihao Liu, Ming Zhang, Yangting Sun, Boxiao Liu, Guanglu Song, Yu Liu, Hongsheng Li

Further, an architecture knowledge pool together with a block similarity function is proposed to utilize parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search +1

Partial Feature Selection and Alignment for Multi-Source Domain Adaptation

no code implementations CVPR 2021 Yangye Fu, Ming Zhang, Xing Xu, Zuo Cao, Chao Ma, Yanli Ji, Kai Zuo, Huimin Lu

By assuming that the source and target domains share consistent key feature representations and identical label space, existing studies on MSDA typically utilize the entire union set of features from both the source and target domains to obtain the feature map and align the map for each category and domain.

feature selection Partial Domain Adaptation

RangeIoUDet: Range Image Based Real-Time 3D Object Detector Optimized by Intersection Over Union

no code implementations CVPR 2021 Zhidong Liang, Zehan Zhang, Ming Zhang, Xian Zhao, ShiLiang Pu

Benefiting from the dense representation of the range image, RangeIoUDet is entirely constructed based on 2D convolution, making it possible to have a fast inference speed.

3D Object Detection Autonomous Driving +2

NoiGAN: NOISE AWARE KNOWLEDGE GRAPH EMBEDDING WITH GAN

no code implementations25 Sep 2019 Kewei Cheng, Yikai Zhu, Ming Zhang, Yizhou Sun

Knowledge graph has gained increasing attention in recent years for its successful applications of numerous tasks.

Knowledge Graph Embedding

A Probabilistic Model-Based Robust Waveform Design for MIMO Radar Detection

no code implementations9 Apr 2022 Xuyang Wang, Bo Tang, Ming Zhang

This paper addresses robust waveform design for multiple-input-multiple-output (MIMO) radar detection.

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

no code implementations21 May 2022 Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang

This problem is typically solved by using graph neural networks (GNNs), which yet rely on a large number of labeled graphs for training and are unable to leverage unlabeled graphs.

Graph Classification

Taxonomy and evolution predicting using deep learning in images

1 code implementation28 Jun 2022 Jiewen Xiao, Wenbin Liao, Ming Zhang, Jing Wang, Jianxin Wang, Yihua Yang

Molecular and morphological characters, as important parts of biological taxonomy, are contradictory but need to be integrated.

Fine-Grained Image Recognition Zero-Shot Learning

Focus-Driven Contrastive Learniang for Medical Question Summarization

1 code implementation1 Sep 2022 Ming Zhang, Shuai Dou, Ziyang Wang, Yunfang Wu

Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers.

Contrastive Learning Sentence

Focus-Driven Contrastive Learning for Medical Question Summarization

no code implementations COLING 2022 Ming Zhang, Shuai Dou, Ziyang Wang, Yunfang Wu

Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers.

Contrastive Learning Sentence

GLCC: A General Framework for Graph-Level Clustering

no code implementations21 Oct 2022 Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang

In this paper, we propose a general graph-level clustering framework named Graph-Level Contrastive Clustering (GLCC) given multiple graphs.

Clustering Contrastive Learning +2

TIER-A: Denoising Learning Framework for Information Extraction

no code implementations13 Nov 2022 Yongkang Li, Ming Zhang

Our framework consists of several neural models with identical structures.

Denoising

2D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraints

no code implementations5 Dec 2022 Zhangjian Ji, Zilong Wang, Ming Zhang, Yapeng Chen, Yuhua Qian

Recently, human pose estimation mainly focuses on how to design a more effective and better deep network structure as human features extractor, and most designed feature extraction networks only introduce the position of each anatomical keypoint to guide their training process.

2D Human Pose Estimation Pose Estimation

A Comprehensive Survey on Deep Graph Representation Learning

no code implementations11 Apr 2023 Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining.

Graph Embedding Graph Representation Learning

Learning Graph ODE for Continuous-Time Sequential Recommendation

no code implementations14 Apr 2023 Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang

Technically, GDERec is characterized by an autoregressive graph ordinary differential equation consisting of two components, which are parameterized by two tailored graph neural networks (GNNs) respectively to capture user preference from the perspective of hybrid dynamical systems.

Sequential Recommendation

TGNN: A Joint Semi-supervised Framework for Graph-level Classification

no code implementations23 Apr 2023 Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang

The two twin modules collaborate with each other by exchanging instance similarity knowledge to fully explore the structure information of both labeled and unlabeled data.

Graph Classification

MolXPT: Wrapping Molecules with Text for Generative Pre-training

no code implementations18 May 2023 Zequn Liu, Wei zhang, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Ming Zhang, Tie-Yan Liu

Considering that text is the most important record for scientific discovery, in this paper, we propose MolXPT, a unified language model of text and molecules pre-trained on SMILES (a sequence representation of molecules) wrapped by text.

Language Modelling Molecular Property Prediction +3

Towards Semi-supervised Universal Graph Classification

no code implementations31 May 2023 Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang

To tackle class shifts, we estimate the certainty of unlabeled graphs using multiple subgraphs, which facilities the discovery of unlabeled data from unknown categories.

Graph Classification

Learning on Graphs under Label Noise

no code implementations14 Jun 2023 Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang

Since this regularization term cannot utilize label information, it can enhance the robustness of node representations to label noise.

Anomaly Detection Contrastive Learning +2

RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification

no code implementations4 Aug 2023 Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang

Recent approaches mainly focus on re-balancing different classes during model training, which fails to explicitly introduce new knowledge and sacrifices the performance of the head classes.

Graph Classification Retrieval

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts

no code implementations31 Aug 2023 Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang

Graph classification, aiming at learning the graph-level representations for effective class assignments, has received outstanding achievements, which heavily relies on high-quality datasets that have balanced class distribution.

Contrastive Learning Graph Classification +2

Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting

no code implementations21 Sep 2023 Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang

This paper studies the problem of traffic flow forecasting, which aims to predict future traffic conditions on the basis of road networks and traffic conditions in the past.

ALEX: Towards Effective Graph Transfer Learning with Noisy Labels

no code implementations26 Sep 2023 Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang

Nevertheless, the majority of GNN-based approaches have been examined using well-annotated benchmark datasets, leading to suboptimal performance in real-world graph learning scenarios.

Contrastive Learning Graph Learning +2

A Survey on Graph Neural Networks in Intelligent Transportation Systems

no code implementations1 Jan 2024 Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang

However, most of the research in this area is still concentrated on traffic forecasting, while other ITS domains, such as autonomous vehicles and urban planning, still require more attention.

Autonomous Vehicles

Reframing Tax Law Entailment as Analogical Reasoning

no code implementations12 Jan 2024 Xinrui Zou, Ming Zhang, Nathaniel Weir, Benjamin Van Durme, Nils Holzenberger

We re-frame statutory reasoning as an analogy task, where each instance of the analogy task involves a combination of two instances of statutory reasoning.

Retrieval

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering

no code implementations23 Jan 2024 Yifang Qin, Wei Ju, Xiao Luo, Yiyang Gu, Zhiping Xiao, Ming Zhang

Collaborative Filtering (CF) is a pivotal research area in recommender systems that capitalizes on collaborative similarities between users and items to provide personalized recommendations.

Collaborative Filtering Recommendation Systems

GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling

no code implementations29 Jan 2024 Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang

Self-supervised graph representation learning has recently shown considerable promise in a range of fields, including bioinformatics and social networks.

Adversarial Robustness Contrastive Learning +3

A Survey of Data-Efficient Graph Learning

no code implementations1 Feb 2024 Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang

Graph-structured data, prevalent in domains ranging from social networks to biochemical analysis, serve as the foundation for diverse real-world systems.

Graph Learning

RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning

no code implementations19 Feb 2024 Congyun Jin, Ming Zhang, Xiaowei Ma, Li Yujiao, Yingbo Wang, Yabo Jia, Yuliang Du, Tao Sun, Haowen Wang, Cong Fan, Jinjie Gu, Chenfei Chi, Xiangguo Lv, Fangzhou Li, Wei Xue, Yiran Huang

Recent advancements in Large Language Models (LLMs) and Large Multi-modal Models (LMMs) have shown potential in various medical applications, such as Intelligent Medical Diagnosis.

document understanding Medical Diagnosis +1

Measuring Vision-Language STEM Skills of Neural Models

no code implementations27 Feb 2024 Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang

Compared to existing datasets that often focus on examining expert-level ability, our dataset includes fundamental skills and questions designed based on the K-12 curriculum.

Math

CURSOR: Scalable Mixed-Order Hypergraph Matching with CUR Decomposition

no code implementations26 Feb 2024 Qixuan Zheng, Ming Zhang, Hong Yan

To achieve greater accuracy, hypergraph matching algorithms require exponential increases in computational resources.

Graph Matching Hypergraph Matching +1

COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting

no code implementations2 Mar 2024 Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang

Toward this end, this paper proposes Conjoint Spatio-Temporal graph neural network (abbreviated as COOL), which models heterogeneous graphs from prior and posterior information to conjointly capture high-order spatio-temporal relationships.

A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges

no code implementations7 Mar 2024 Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang

To tackle these issues, substantial efforts have been devoted to improving the performance of GNN models in practical real-world scenarios, as well as enhancing their reliability and robustness.

Fraud Detection

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

no code implementations8 Mar 2024 Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross Mcilroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, Luke Vilnis, Oscar Chang, Nobuyuki Morioka, George Tucker, Ce Zheng, Oliver Woodman, Nithya Attaluri, Tomas Kocisky, Evgenii Eltyshev, Xi Chen, Timothy Chung, Vittorio Selo, Siddhartha Brahma, Petko Georgiev, Ambrose Slone, Zhenkai Zhu, James Lottes, Siyuan Qiao, Ben Caine, Sebastian Riedel, Alex Tomala, Martin Chadwick, Juliette Love, Peter Choy, Sid Mittal, Neil Houlsby, Yunhao Tang, Matthew Lamm, Libin Bai, Qiao Zhang, Luheng He, Yong Cheng, Peter Humphreys, Yujia Li, Sergey Brin, Albin Cassirer, Yingjie Miao, Lukas Zilka, Taylor Tobin, Kelvin Xu, Lev Proleev, Daniel Sohn, Alberto Magni, Lisa Anne Hendricks, Isabel Gao, Santiago Ontañón, Oskar Bunyan, Nathan Byrd, Abhanshu Sharma, Biao Zhang, Mario Pinto, Rishika Sinha, Harsh Mehta, Dawei Jia, Sergi Caelles, Albert Webson, Alex Morris, Becca Roelofs, Yifan Ding, Robin Strudel, Xuehan Xiong, Marvin Ritter, Mostafa Dehghani, Rahma Chaabouni, Abhijit Karmarkar, Guangda Lai, Fabian Mentzer, Bibo Xu, Yaguang Li, Yujing Zhang, Tom Le Paine, Alex Goldin, Behnam Neyshabur, Kate Baumli, Anselm Levskaya, Michael Laskin, Wenhao Jia, Jack W. Rae, Kefan Xiao, Antoine He, Skye Giordano, Lakshman Yagati, Jean-Baptiste Lespiau, Paul Natsev, Sanjay Ganapathy, Fangyu Liu, Danilo Martins, Nanxin Chen, Yunhan Xu, Megan Barnes, Rhys May, Arpi Vezer, Junhyuk Oh, Ken Franko, Sophie Bridgers, Ruizhe Zhao, Boxi Wu, Basil Mustafa, Sean Sechrist, Emilio Parisotto, Thanumalayan Sankaranarayana Pillai, Chris Larkin, Chenjie Gu, Christina Sorokin, Maxim Krikun, Alexey Guseynov, Jessica Landon, Romina Datta, Alexander Pritzel, Phoebe Thacker, Fan Yang, Kevin Hui, Anja Hauth, Chih-Kuan Yeh, David Barker, Justin Mao-Jones, Sophia Austin, Hannah Sheahan, Parker Schuh, James Svensson, Rohan Jain, Vinay Ramasesh, Anton Briukhov, Da-Woon Chung, Tamara von Glehn, Christina Butterfield, Priya Jhakra, Matthew Wiethoff, Justin Frye, Jordan Grimstad, Beer Changpinyo, Charline Le Lan, Anna Bortsova, Yonghui Wu, Paul Voigtlaender, Tara Sainath, Charlotte Smith, Will Hawkins, Kris Cao, James Besley, Srivatsan Srinivasan, Mark Omernick, Colin Gaffney, Gabriela Surita, Ryan Burnell, Bogdan Damoc, Junwhan Ahn, Andrew Brock, Mantas Pajarskas, Anastasia Petrushkina, Seb Noury, Lorenzo Blanco, Kevin Swersky, Arun Ahuja, Thi Avrahami, Vedant Misra, Raoul de Liedekerke, Mariko Iinuma, Alex Polozov, Sarah York, George van den Driessche, Paul Michel, Justin Chiu, Rory Blevins, Zach Gleicher, Adrià Recasens, Alban Rrustemi, Elena Gribovskaya, Aurko Roy, Wiktor Gworek, Séb Arnold, Lisa Lee, James Lee-Thorp, Marcello Maggioni, Enrique Piqueras, Kartikeya Badola, Sharad Vikram, Lucas Gonzalez, Anirudh Baddepudi, Evan Senter, Jacob Devlin, James Qin, Michael Azzam, Maja Trebacz, Martin Polacek, Kashyap Krishnakumar, Shuo-Yiin Chang, Matthew Tung, Ivo Penchev, Rishabh Joshi, Kate Olszewska, Carrie Muir, Mateo Wirth, Ale Jakse Hartman, Josh Newlan, Sheleem Kashem, Vijay Bolina, Elahe Dabir, Joost van Amersfoort, Zafarali Ahmed, James Cobon-Kerr, Aishwarya Kamath, Arnar Mar Hrafnkelsson, Le Hou, Ian Mackinnon, Alexandre Frechette, Eric Noland, Xiance Si, Emanuel Taropa, Dong Li, Phil Crone, Anmol Gulati, Sébastien Cevey, Jonas Adler, Ada Ma, David Silver, Simon Tokumine, Richard Powell, Stephan Lee, Michael Chang, Samer Hassan, Diana Mincu, Antoine Yang, Nir Levine, Jenny Brennan, Mingqiu Wang, Sarah Hodkinson, Jeffrey Zhao, Josh Lipschultz, Aedan Pope, Michael B. Chang, Cheng Li, Laurent El Shafey, Michela Paganini, Sholto Douglas, Bernd Bohnet, Fabio Pardo, Seth Odoom, Mihaela Rosca, Cicero Nogueira dos santos, Kedar Soparkar, Arthur Guez, Tom Hudson, Steven Hansen, Chulayuth Asawaroengchai, Ravi Addanki, Tianhe Yu, Wojciech Stokowiec, Mina Khan, Justin Gilmer, Jaehoon Lee, Carrie Grimes Bostock, Keran Rong, Jonathan Caton, Pedram Pejman, Filip Pavetic, Geoff Brown, Vivek Sharma, Mario Lučić, Rajkumar Samuel, Josip Djolonga, Amol Mandhane, Lars Lowe Sjösund, Elena Buchatskaya, Elspeth White, Natalie Clay, Jiepu Jiang, Hyeontaek Lim, Ross Hemsley, Jane Labanowski, Nicola De Cao, David Steiner, Sayed Hadi Hashemi, Jacob Austin, Anita Gergely, Tim Blyth, Joe Stanton, Kaushik Shivakumar, Aditya Siddhant, Anders Andreassen, Carlos Araya, Nikhil Sethi, Rakesh Shivanna, Steven Hand, Ankur Bapna, Ali Khodaei, Antoine Miech, Garrett Tanzer, Andy Swing, Shantanu Thakoor, Zhufeng Pan, Zachary Nado, Stephanie Winkler, Dian Yu, Mohammad Saleh, Loren Maggiore, Iain Barr, Minh Giang, Thais Kagohara, Ivo Danihelka, Amit Marathe, Vladimir Feinberg, Nimesh Ghelani, Dan Horgan, Helen Miller, Lexi Walker, Richard Tanburn, Mukarram Tariq, Disha Shrivastava, Fei Xia, Chung-Cheng Chiu, Khuslen Baatarsukh, Sina Samangooei, Fred Alcober, Axel Stjerngren, Paul Komarek, Katerina Tsihlas, Anudhyan Boral, Ramona Comanescu, Jeremy Chen, Ruibo Liu, Dawn Bloxwich, Charlie Chen, Yanhua Sun, Fangxiaoyu Feng, Matthew Mauger, Xerxes Dotiwalla, Vincent Hellendoorn, Michael Sharman, Ivy Zheng, Krishna Haridasan, Gabe Barth-Maron, Craig Swanson, Dominika Rogozińska, Alek Andreev, Paul Kishan Rubenstein, Ruoxin Sang, Dan Hurt, Gamaleldin Elsayed, Renshen Wang, Dave Lacey, Anastasija Ilić, Yao Zhao, Lora Aroyo, Chimezie Iwuanyanwu, Vitaly Nikolaev, Balaji Lakshminarayanan, Sadegh Jazayeri, Raphaël Lopez Kaufman, Mani Varadarajan, Chetan Tekur, Doug Fritz, Misha Khalman, David Reitter, Kingshuk Dasgupta, Shourya Sarcar, Tina Ornduff, Javier Snaider, Fantine Huot, Johnson Jia, Rupert Kemp, Nejc Trdin, Anitha Vijayakumar, Lucy Kim, Christof Angermueller, Li Lao, Tianqi Liu, Haibin Zhang, David Engel, Somer Greene, Anaïs White, Jessica Austin, Lilly Taylor, Shereen Ashraf, Dangyi Liu, Maria Georgaki, Irene Cai, Yana Kulizhskaya, Sonam Goenka, Brennan Saeta, Kiran Vodrahalli, Christian Frank, Dario de Cesare, Brona Robenek, Harry Richardson, Mahmoud Alnahlawi, Christopher Yew, Priya Ponnapalli, Marco Tagliasacchi, Alex Korchemniy, Yelin Kim, Dinghua Li, Bill Rosgen, Zoe Ashwood, Kyle Levin, Jeremy Wiesner, Praseem Banzal, Praveen Srinivasan, Hongkun Yu, Çağlar Ünlü, David Reid, Zora Tung, Daniel Finchelstein, Ravin Kumar, Andre Elisseeff, Jin Huang, Ming Zhang, Rui Zhu, Ricardo Aguilar, Mai Giménez, Jiawei Xia, Olivier Dousse, Willi Gierke, Soheil Hassas Yeganeh, Damion Yates, Komal Jalan, Lu Li, Eri Latorre-Chimoto, Duc Dung Nguyen, Ken Durden, Praveen Kallakuri, Yaxin Liu, Matthew Johnson, Tomy Tsai, Alice Talbert, Jasmine Liu, Alexander Neitz, Chen Elkind, Marco Selvi, Mimi Jasarevic, Livio Baldini Soares, Albert Cui, Pidong Wang, Alek Wenjiao Wang, Xinyu Ye, Krystal Kallarackal, Lucia Loher, Hoi Lam, Josef Broder, Dan Holtmann-Rice, Nina Martin, Bramandia Ramadhana, Daniel Toyama, Mrinal Shukla, Sujoy Basu, Abhi Mohan, Nick Fernando, Noah Fiedel, Kim Paterson, Hui Li, Ankush Garg, Jane Park, DongHyun Choi, Diane Wu, Sankalp Singh, Zhishuai Zhang, Amir Globerson, Lily Yu, John Carpenter, Félix de Chaumont Quitry, Carey Radebaugh, Chu-Cheng Lin, Alex Tudor, Prakash Shroff, Drew Garmon, Dayou Du, Neera Vats, Han Lu, Shariq Iqbal, Alex Yakubovich, Nilesh Tripuraneni, James Manyika, Haroon Qureshi, Nan Hua, Christel Ngani, Maria Abi Raad, Hannah Forbes, Anna Bulanova, Jeff Stanway, Mukund Sundararajan, Victor Ungureanu, Colton Bishop, Yunjie Li, Balaji Venkatraman, Bo Li, Chloe Thornton, Salvatore Scellato, Nishesh Gupta, Yicheng Wang, Ian Tenney, Xihui Wu, Ashish Shenoy, Gabriel Carvajal, Diana Gage Wright, Ben Bariach, Zhuyun Xiao, Peter Hawkins, Sid Dalmia, Clement Farabet, Pedro Valenzuela, Quan Yuan, Chris Welty, Ananth Agarwal, Mia Chen, Wooyeol Kim, Brice Hulse, Nandita Dukkipati, Adam Paszke, Andrew Bolt, Elnaz Davoodi, Kiam Choo, Jennifer Beattie, Jennifer Prendki, Harsha Vashisht, Rebeca Santamaria-Fernandez, Luis C. Cobo, Jarek Wilkiewicz, David Madras, Ali Elqursh, Grant Uy, Kevin Ramirez, Matt Harvey, Tyler Liechty, Heiga Zen, Jeff Seibert, Clara Huiyi Hu, Mohamed Elhawaty, Andrey Khorlin, Maigo Le, Asaf Aharoni, Megan Li, Lily Wang, Sandeep Kumar, Alejandro Lince, Norman Casagrande, Jay Hoover, Dalia El Badawy, David Soergel, Denis Vnukov, Matt Miecnikowski, Jiri Simsa, Anna Koop, Praveen Kumar, Thibault Sellam, Daniel Vlasic, Samira Daruki, Nir Shabat, John Zhang, Guolong Su, Jiageng Zhang, Jeremiah Liu, Yi Sun, Evan Palmer, Alireza Ghaffarkhah, Xi Xiong, Victor Cotruta, Michael Fink, Lucas Dixon, Ashwin Sreevatsa, Adrian Goedeckemeyer, Alek Dimitriev, Mohsen Jafari, Remi Crocker, Nicholas FitzGerald, Aviral Kumar, Sanjay Ghemawat, Ivan Philips, Frederick Liu, Yannie Liang, Rachel Sterneck, Alena Repina, Marcus Wu, Laura Knight, Marin Georgiev, Hyo Lee, Harry Askham, Abhishek Chakladar, Annie Louis, Carl Crous, Hardie Cate, Dessie Petrova, MICHAEL QUINN, Denese Owusu-Afriyie, Achintya Singhal, Nan Wei, Solomon Kim, Damien Vincent, Milad Nasr, Christopher A. Choquette-Choo, Reiko Tojo, Shawn Lu, Diego de Las Casas, Yuchung Cheng, Tolga Bolukbasi, Katherine Lee, Saaber Fatehi, Rajagopal Ananthanarayanan, Miteyan Patel, Charbel Kaed, Jing Li, Jakub Sygnowski, Shreyas Rammohan Belle, Zhe Chen, Jaclyn Konzelmann, Siim Põder, Roopal Garg, Vinod Koverkathu, Adam Brown, Chris Dyer, Rosanne Liu, Azade Nova, Jun Xu, Slav Petrov, Demis Hassabis, Koray Kavukcuoglu, Jeffrey Dean, Oriol Vinyals

In this report, we present the latest model of the Gemini family, Gemini 1. 5 Pro, a highly compute-efficient multimodal mixture-of-experts model capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio.

Code Generation Retrieval

Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment

no code implementations11 Mar 2024 Ming Zhang, Ke Chang, Yunfang Wu

Multi-modal semantic understanding requires integrating information from different modalities to extract users' real intention behind words.

Contrastive Learning Sarcasm Detection +1

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