Search Results for author: Jiawei Liu

Found 81 papers, 40 papers with code

Magicoder: Source Code Is All You Need

1 code implementation4 Dec 2023 Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, Lingming Zhang

Magicoder models are trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets to generate high-quality instruction data for code.

Code Generation Text-to-Code Generation

Fast and Flexible Human Pose Estimation with HyperPose

1 code implementation26 Aug 2021 Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong

When it comes to customising these algorithms for real-world applications, none of the existing libraries can offer both the flexibility of developing custom pose estimation algorithms and the high-performance of executing these algorithms on commodity devices.

Pose Estimation

MotionDirector: Motion Customization of Text-to-Video Diffusion Models

1 code implementation12 Oct 2023 Rui Zhao, YuChao Gu, Jay Zhangjie Wu, David Junhao Zhang, Jiawei Liu, Weijia Wu, Jussi Keppo, Mike Zheng Shou

Given a set of video clips of the same motion concept, the task of Motion Customization is to adapt existing text-to-video diffusion models to generate videos with this motion.

RPTQ: Reorder-based Post-training Quantization for Large Language Models

1 code implementation3 Apr 2023 Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu

In this paper, we identify that the challenge in quantizing activations in LLMs arises from varying ranges across channels, rather than solely the presence of outliers.

Quantization

Residual Denoising Diffusion Models

1 code implementation25 Aug 2023 Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu

We propose residual denoising diffusion models (RDDM), a novel dual diffusion process that decouples the traditional single denoising diffusion process into residual diffusion and noise diffusion.

Denoising Image Generation +2

Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework

1 code implementation4 Mar 2021 Cheng Yang, Jiawei Liu, Chuan Shi

Our framework extracts the knowledge of an arbitrary learned GNN model (teacher model), and injects it into a well-designed student model.

Knowledge Distillation Node Classification

DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations

1 code implementation11 Mar 2024 Tianhao Qi, Shancheng Fang, Yanze Wu, Hongtao Xie, Jiawei Liu, Lang Chen, Qian He, Yongdong Zhang

The Q-Formers are trained using paired images rather than the identical target, in which the reference image and the ground-truth image are with the same style or semantics.

Disentanglement

Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes

1 code implementation28 Jan 2024 Weifeng Liu, Tianyi She, Jiawei Liu, Run Wang, Dongyu Yao, Ziyou Liang

In recent years, DeepFake technology has achieved unprecedented success in high-quality video synthesis, whereas these methods also pose potential and severe security threats to humanity.

DeepFake Detection Face Swapping

PD-Quant: Post-Training Quantization based on Prediction Difference Metric

1 code implementation CVPR 2023 Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu

It determines the quantization parameters by using the information of differences between network prediction before and after quantization.

Neural Network Compression Quantization

NeuRI: Diversifying DNN Generation via Inductive Rule Inference

1 code implementation4 Feb 2023 Jiawei Liu, Jinjun Peng, Yuyao Wang, Lingming Zhang

NeuRI finds 100 new bugs for PyTorch and TensorFlow in four months, with 81 already fixed or confirmed.

Decision Making Program Synthesis +1

Local Label Point Correction for Edge Detection of Overlapping Cervical Cells

1 code implementation5 Oct 2020 Jiawei Liu, Huijie Fan, Qiang Wang, Wentao Li, Yandong Tang, Danbo Wang, Mingyi Zhou, Li Chen

The qualitative and quantitative experimental results show that our LLPC can improve the quality of manual labels and the accuracy of overlapping cell edge detection.

Cell Segmentation Edge Detection +2

White-box Compiler Fuzzing Empowered by Large Language Models

1 code implementation24 Oct 2023 Chenyuan Yang, Yinlin Deng, Runyu Lu, Jiayi Yao, Jiawei Liu, Reyhaneh Jabbarvand, Lingming Zhang

Nonetheless, prompting LLMs with compiler source-code information remains a missing piece of research in compiler testing.

Code Generation Compiler Optimization

Confidence-Aware Learning for Camouflaged Object Detection

1 code implementation22 Jun 2021 Jiawei Liu, Jing Zhang, Nick Barnes

Then, we concatenate it with the input image and feed it to the confidence estimation network to produce an one channel confidence map. We generate dynamic supervision for the confidence estimation network, representing the agreement of camouflage prediction with the ground truth camouflage map.

Object object-detection +1

Automated Essay Scoring based on Two-Stage Learning

2 code implementations23 Jan 2019 Jiawei Liu, Yang Xu, Yaguang Zhu

Current state-of-art feature-engineered and end-to-end Automated Essay Score (AES) methods are proven to be unable to detect adversarial samples, e. g. the essays composed of permuted sentences and the prompt-irrelevant essays.

Automated Essay Scoring Vocal Bursts Valence Prediction

Coverage-Guided Tensor Compiler Fuzzing with Joint IR-Pass Mutation

1 code implementation21 Feb 2022 Jiawei Liu, Yuxiang Wei, Sen yang, Yinlin Deng, Lingming Zhang

Our results show that Tzer substantially outperforms existing fuzzing techniques on tensor compiler testing, with 75% higher coverage and 50% more valuable tests than the 2nd-best technique.

A Decoupled Multi-Task Network for Shadow Removal

1 code implementation IEEE Transactions on Multimedia 2023 Jiawei Liu, Qiang Wang, Huijie Fan, Wentao Li, Liangqiong Qu, Yandong Tang

Last, these features are converted to a target shadow-free image, affiliated shadow matte, and shadow image, supervised by multi-task joint loss functions.

Image Reconstruction Image Shadow Removal +1

Calibrated Feature Decomposition for Generalizable Person Re-Identification

1 code implementation27 Nov 2021 Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha

The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.

Domain Generalization Generalizable Person Re-identification

NNSmith: Generating Diverse and Valid Test Cases for Deep Learning Compilers

1 code implementation26 Jul 2022 Jiawei Liu, JinKun Lin, Fabian Ruffy, Cheng Tan, Jinyang Li, Aurojit Panda, Lingming Zhang

In this work, we propose a new fuzz testing approach for finding bugs in deep-learning compilers.

valid

A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis

1 code implementation EMNLP 2021 Jiawei Liu, Kaisong Song, Yangyang Kang, Guoxiu He, Zhuoren Jiang, Changlong Sun, Wei Lu, Xiaozhong Liu

Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension.

Chatbot Multi-Task Learning

Self-Refined Large Language Model as Automated Reward Function Designer for Deep Reinforcement Learning in Robotics

1 code implementation13 Sep 2023 Jiayang Song, Zhehua Zhou, Jiawei Liu, Chunrong Fang, Zhan Shu, Lei Ma

Then, the performance of the reward function is assessed, and the results are presented back to the LLM for guiding its self-refinement process.

Common Sense Reasoning Language Modelling +1

Sounding Video Generator: A Unified Framework for Text-guided Sounding Video Generation

1 code implementation29 Mar 2023 Jiawei Liu, Weining Wang, Sihan Chen, Xinxin Zhu, Jing Liu

In this work, we concentrate on a rarely investigated problem of text guided sounding video generation and propose the Sounding Video Generator (SVG), a unified framework for generating realistic videos along with audio signals.

Audio Generation Contrastive Learning +1

Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NAS

1 code implementation13 Jun 2022 Jiawei Liu, Kaiyu Zhang, Weitai Hu, Qing Yang

To address this problem, we propose a step-by-step training super-net scheme from one-shot NAS to few-shot NAS.

Neural Architecture Search

Learning structure-aware semantic segmentation with image-level supervision

1 code implementation15 Apr 2021 Jiawei Liu, Jing Zhang, Yicong Hong, Nick Barnes

Within this pipeline, the class activation map (CAM) is obtained and further processed to serve as a pseudo label to train the semantic segmentation model in a fully-supervised manner.

Boundary Detection Common Sense Reasoning +4

LF Tracy: A Unified Single-Pipeline Approach for Salient Object Detection in Light Field Cameras

1 code implementation30 Jan 2024 Fei Teng, Jiaming Zhang, Jiawei Liu, Kunyu Peng, Xina Cheng, Zhiyong Li, Kailun Yang

Previous approaches predominantly employ a custom two-stream design to discover the implicit angular feature within light field cameras, leading to significant information isolation between different LF representations.

Data Augmentation object-detection +2

Let's Learn Step by Step: Enhancing In-Context Learning Ability with Curriculum Learning

1 code implementation16 Feb 2024 Yinpeng Liu, Jiawei Liu, Xiang Shi, Qikai Cheng, Wei Lu

We advocate the few-shot in-context curriculum learning (ICCL), a simple but effective demonstration ordering method for ICL, which implies gradually increasing the complexity of prompt demonstrations during the inference process.

In-Context Learning

Machine Translation Testing via Syntactic Tree Pruning

1 code implementation1 Jan 2024 Quanjun Zhang, Juan Zhai, Chunrong Fang, Jiawei Liu, Weisong Sun, Haichuan Hu, Qingyu Wang

The results show that STP can accurately find 5, 073 unique erroneous translations in Google Translate and 5, 100 unique erroneous translations in Bing Microsoft Translator (400% more than state-of-the-art techniques), with 64. 5% and 65. 4% precision, respectively.

Machine Translation Sentence +1

Enhanced countering adversarial attacks via input denoising and feature restoring

1 code implementation19 Nov 2021 Yanni Li, Wenhui Zhang, Jiawei Liu, Xiaoli Kou, Hui Li, Jiangtao Cui

Despite the fact that deep neural networks (DNNs) have achieved prominent performance in various applications, it is well known that DNNs are vulnerable to adversarial examples/samples (AEs) with imperceptible perturbations in clean/original samples.

Adversarial Attack Denoising

Model Calibration in Dense Classification with Adaptive Label Perturbation

1 code implementation ICCV 2023 Jiawei Liu, Changkun Ye, Shan Wang, Ruikai Cui, Jing Zhang, Kaihao Zhang, Nick Barnes

To improve model calibration, we propose Adaptive Stochastic Label Perturbation (ASLP) which learns a unique label perturbation level for each training image.

Binary Classification Classification +1

Endowing Pre-trained Graph Models with Provable Fairness

1 code implementation19 Feb 2024 Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi

Furthermore, with GraphPAR, we quantify whether the fairness of each node is provable, i. e., predictions are always fair within a certain range of sensitive attribute semantics.

Attribute Fairness +1

Implicitly Incorporating Morphological Information into Word Embedding

no code implementations10 Jan 2017 Yang Xu, Jiawei Liu

In this paper, we propose three novel models to enhance word embedding by implicitly using morphological information.

Word Similarity

CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification

no code implementations19 Nov 2018 Jiawei Liu, Zheng-Jun Zha, Hongtao Xie, Zhiwei Xiong, Yongdong Zhang

An appearance network is developed to learn appearance features from the full body, horizontal and vertical body parts of pedestrians with spatial dependencies among body parts.

Attribute Multi-Task Learning +1

Adaptive Transfer Network for Cross-Domain Person Re-Identification

no code implementations CVPR 2019 Jiawei Liu, Zheng-Jun Zha, Di Chen, Richang Hong, Meng Wang

In particular, ATNet consists of a transfer network composed by multiple factor-wise CycleGANs and an ensemble CycleGAN as well as a selection network that infers the affects of different factors on transferring each image.

Person Re-Identification Style Transfer

Co-Saliency Spatio-Temporal Interaction Network for Person Re-Identification in Videos

no code implementations10 Apr 2020 Jiawei Liu, Zheng-Jun Zha, Xierong Zhu, Na Jiang

Person re-identification aims at identifying a certain pedestrian across non-overlapping camera networks.

Person Re-Identification

Revisiting Regex Generation for Modeling Industrial Applications by Incorporating Byte Pair Encoder

no code implementations6 May 2020 De-Sheng Wang, Jiawei Liu, Xiang Qi, Baolin Sun, Peng Zhang

The results demonstrate the effectiveness of our method, which outperforms the baseline on 10 kinds of data and achieves nearly 50 percent improvement on average.

Co-Designing Statistical MIMO Radar and In-band Full-Duplex Multi-User MIMO Communications -- Part I: Signal Processing

no code implementations26 Jun 2020 Jiawei Liu, Kumar Vijay Mishra, Mohammad Saquib

We consider a spectral sharing problem in which a statistical (or widely distributed) multiple-input multiple-output (MIMO) radar and an in-band full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system concurrently operate within the same frequency band.

Decorrelated Clustering with Data Selection Bias

1 code implementation29 Jun 2020 Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang

Most of existing clustering algorithms are proposed without considering the selection bias in data.

Clustering Selection bias

Temporal Attribute-Appearance Learning Network for Video-based Person Re-Identification

no code implementations9 Sep 2020 Jiawei Liu, Xierong Zhu, Zheng-Jun Zha

TALNet simultaneously exploits human attributes and appearance to learn comprehensive and effective pedestrian representations from videos.

Attribute Multi-Task Learning +1

Hierarchical Gumbel Attention Network for Text-based Person Search

no code implementations10 Oct 2020 Kecheng Zheng, Wu Liu, Jiawei Liu, Zheng-Jun Zha, Tao Mei

This hard selection strategy is able to fuse the strong-relevant multi-modality features for alleviating the problem of matching redundancy.

Image Retrieval Image-to-Text Retrieval +6

Adaptive Domain-Specific Normalization for Generalizable Person Re-Identification

no code implementations7 May 2021 Jiawei Liu, Zhipeng Huang, Kecheng Zheng, Dong Liu, Xiaoyan Sun, Zheng-Jun Zha

It describes unseen target domain as a combination of the known source ones, and explicitly learns domain-specific representation with target distribution to improve the model's generalization by a meta-learning pipeline.

Generalizable Person Re-identification Meta-Learning

ECNUICA at SemEval-2021 Task 11: Rule based Information Extraction Pipeline

no code implementations SEMEVAL 2021 Jiaju Lin, Jing Ling, Zhiwei Wang, Jiawei Liu, Qin Chen, Liang He

The purpose of the task was to extract triples from a paper in the Nature Language Processing field for constructing an Open Research Knowledge Graph.

Open Information Extraction

A Two-Stage Data-Free Adversarial Patch Generation Framework

no code implementations29 Sep 2021 Jiawei Liu, Hang Gao, Yunfeng Hu, Xun Gong

The proxy dataset selection stage calculates the proposed average patch saliency (APS) of each available dataset to select a high-APS proxy dataset that can guarantee patches' fooling abilities.

Vocal Bursts Valence Prediction

Semi-supervised Salient Object Detection with Effective Confidence Estimation

no code implementations28 Dec 2021 Jiawei Liu, Jing Zhang, Nick Barnes

We study semi-supervised salient object detection, with access to a small number of labeled samples and a large number of unlabeled samples.

Object object-detection +3

Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification

no code implementations3 Mar 2022 Zhipeng Huang, Jiawei Liu, Liang Li, Kecheng Zheng, Zheng-Jun Zha

RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images.

Person Re-Identification

Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification

no code implementations3 Mar 2022 Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha

In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers as a dynamically self-refining Gaussian process to alleviate the bias to unseen domain for improving the generalization.

Generalizable Person Re-identification Representation Learning

Realizing Ultra-Fast and Energy-Efficient Baseband Processing Using Analogue Resistive Switching Memory

no code implementations7 May 2022 Qunsong Zeng, Jiawei Liu, Jun Lan, Yi Gong, Zhongrui Wang, Yida Li, Kaibin Huang

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors.

Label Noise-Resistant Mean Teaching for Weakly Supervised Fake News Detection

no code implementations10 Jun 2022 Jingyi Xie, Jiawei Liu, Zheng-Jun Zha

LNMT leverages unlabeled news and feedback comments of users to enlarge the amount of training data and facilitates model training by generating refined labels as weak supervision.

Fake News Detection Model Optimization

Generalised Co-Salient Object Detection

no code implementations20 Aug 2022 Jiawei Liu, Jing Zhang, Ruikai Cui, Kaihao Zhang, Weihao Li, Nick Barnes

We propose a new setting that relaxes an assumption in the conventional Co-Salient Object Detection (CoSOD) setting by allowing the presence of "noisy images" which do not show the shared co-salient object.

Co-Salient Object Detection Object +3

AI vs. Human -- Differentiation Analysis of Scientific Content Generation

no code implementations24 Jan 2023 Yongqiang Ma, Jiawei Liu, Fan Yi, Qikai Cheng, Yong Huang, Wei Lu, Xiaozhong Liu

We find that there exists a "writing style" gap between AI-generated scientific text and human-written scientific text.

Text Detection

Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Driving

no code implementations8 Feb 2023 Jiawei Liu, Xingping Dong, Sanyuan Zhao, Jianbing Shen

To achieve simultaneous detection for both common and rare objects, we propose a novel task, called generalized few-shot 3D object detection, where we have a large amount of training data for common (base) objects, but only a few data for rare (novel) classes.

3D Object Detection Autonomous Driving +1

Multi-Channel Attentive Feature Fusion for Radio Frequency Fingerprinting

no code implementations19 Mar 2023 Yuan Zeng, Yi Gong, Jiawei Liu, Shangao Lin, Zidong Han, Ruoxiao Cao, Kaibin Huang, Khaled Ben Letaief

The features extracted from different channels are fused adaptively using a shared attention module, where the weights of neural features from multiple channels are learned during training the McAFF model.

Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance

no code implementations23 Mar 2023 Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu

Post-training quantization (PTQ) is a popular method for compressing deep neural networks (DNNs) without modifying their original architecture or training procedures.

Benchmarking Data Augmentation +1

Abnormal Event Detection via Hypergraph Contrastive Learning

no code implementations2 Apr 2023 Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang

AEHCL designs the intra-event and inter-event contrastive modules to exploit self-supervised AHIN information.

Contrastive Learning Event Detection

NPS: A Framework for Accurate Program Sampling Using Graph Neural Network

no code implementations18 Apr 2023 Yuanwei Fang, Zihao Liu, Yanheng Lu, Jiawei Liu, Jiajie Li, Yi Jin, Jian Chen, Yenkuang Chen, Hongzhong Zheng, Yuan Xie

Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.

Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge

no code implementations5 May 2023 Jiawei Liu, Zi Xiong, Yi Jiang, Yongqiang Ma, Wei Lu, Yong Huang, Qikai Cheng

Inspired by recent advancement in prompt learning, in this paper, we propose the Mix Prompt Tuning (MPT), which is a semi-supervised method to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks with a small number of labeled examples.

Sentence

Edge-Aware Regional Message Passing Controller for Image Forgery Localization

no code implementations CVPR 2023 Dong Li, Jiaying Zhu, Menglu Wang, Jiawei Liu, Xueyang Fu, Zheng-Jun Zha

In the second step, guided by the learnable edges, a region message passing controller is devised to weaken the message passing between the forged and authentic regions.

Binarization graph construction

Knowledge-Enhanced Hierarchical Information Correlation Learning for Multi-Modal Rumor Detection

no code implementations28 Jun 2023 Jiawei Liu, Jingyi Xie, Fanrui Zhang, Qiang Zhang, Zheng-Jun Zha

The explosive growth of rumors with text and images on social media platforms has drawn great attention.

Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-trained Vision-Language Models

no code implementations ICCV 2023 Kecheng Zheng, Wei Wu, Ruili Feng, Kai Zhu, Jiawei Liu, Deli Zhao, Zheng-Jun Zha, Wei Chen, Yujun Shen

To bring the useful knowledge back into light, we first identify a set of parameters that are important to a given downstream task, then attach a binary mask to each parameter, and finally optimize these masks on the downstream data with the parameters frozen.

Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G

no code implementations19 Aug 2023 Qunsong Zeng, Jiawei Liu, Mingrui Jiang, Jun Lan, Yi Gong, Zhongrui Wang, Yida Li, Can Li, Jim Ignowski, Kaibin Huang

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors.

Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types

no code implementations15 Oct 2023 Jiahao Xia, Gavin Gong, Jiawei Liu, Zhigang Zhu, Hao Tang

In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data.

Segmentation Zero Shot Segmentation

Towards Graph Foundation Models: A Survey and Beyond

no code implementations18 Oct 2023 Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi

Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains.

Graph Learning

Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher

no code implementations19 Oct 2023 Xiang Shi, Jiawei Liu, Yinpeng Liu, Qikai Cheng, Wei Lu

The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches.

Hallucination Information Retrieval +1

DreamTuner: Single Image is Enough for Subject-Driven Generation

no code implementations21 Dec 2023 Miao Hua, Jiawei Liu, Fei Ding, Wei Liu, Jie Wu, Qian He

Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which require the generation of customized concepts with one or a few reference images.

Text-to-Image Generation

MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation

no code implementations9 Jan 2024 Weimin WANG, Jiawei Liu, Zhijie Lin, Jiangqiao Yan, Shuo Chen, Chetwin Low, Tuyen Hoang, Jie Wu, Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field.

MORPH Video Generation

Multi-perspective Memory Enhanced Network for Identifying Key Nodes in Social Networks

no code implementations22 Mar 2024 Qiang Zhang, Jiawei Liu, Fanrui Zhang, Xiaoling Zhu, Zheng-Jun Zha

Existing key node identification methods usually consider node influence only from the propagation structure perspective and have insufficient generalization ability to unknown scenarios.

Blocking Graph Attention

Hierarchical Information Enhancement Network for Cascade Prediction in Social Networks

no code implementations22 Mar 2024 Fanrui Zhang, Jiawei Liu, Qiang Zhang, Xiaoling Zhu, Zheng-Jun Zha

In this work, we propose a novel Hierarchical Information Enhancement Network (HIENet) for cascade prediction.

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