Search Results for author: Zhen Han

Found 39 papers, 15 papers with code

TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion

1 code implementation spnlp (ACL) 2022 Guirong Fu, Zhao Meng, Zhen Han, Zifeng Ding, Yunpu Ma, Matthias Schubert, Volker Tresp, Roger Wattenhofer

In this paper, we tackle the temporal knowledge graph completion task by proposing TempCaps, which is a Capsule network-based embedding model for Temporal knowledge graph completion.

Entity Embeddings Temporal Knowledge Graph Completion

Multi-Hop Open-Domain Question Answering over Structured and Unstructured Knowledge

no code implementations Findings (NAACL) 2022 Yue Feng, Zhen Han, Mingming Sun, Ping Li

DEHG employs a graph constructor to integrate structured and unstructured information, a context encoder to represent nodes and question, a heterogeneous information reasoning layer to conduct multi-hop reasoning on both information sources, and an answer decoder to generate answers for the question.

Decoder Open-Domain Question Answering

Learning Neural Ordinary Equations for Forecasting Future Links on Temporal Knowledge Graphs

no code implementations EMNLP 2021 Zhen Han, Zifeng Ding, Yunpu Ma, Yujia Gu, Volker Tresp

In addition, a novel graph transition layer is applied to capture the transitions on the dynamic graph, i. e., edge formation and dissolution.

Knowledge Graphs

A rapid approach to urban traffic noise mapping with a generative adversarial network

no code implementations21 May 2024 Xinhao Yang, Zhen Han, Xiaodong Lu, Yuan Zhang

Furthermore, the trained model is integrated into Grasshopper as a tool, facilitating the rapid generation of traffic noise maps.

StyleBooth: Image Style Editing with Multimodal Instruction

1 code implementation18 Apr 2024 Zhen Han, Chaojie Mao, Zeyinzi Jiang, Yulin Pan, Jingfeng Zhang

We integrate encoded textual instruction and image exemplar as a unified condition for diffusion model, enabling the editing of original image following multimodal instructions.

Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?

no code implementations4 Apr 2024 Shuo Chen, Zhen Han, Bailan He, Zifeng Ding, Wenqian Yu, Philip Torr, Volker Tresp, Jindong Gu

Various jailbreak attacks have been proposed to red-team Large Language Models (LLMs) and revealed the vulnerable safeguards of LLMs.

Locate, Assign, Refine: Taming Customized Image Inpainting with Text-Subject Guidance

no code implementations28 Mar 2024 Yulin Pan, Chaojie Mao, Zeyinzi Jiang, Zhen Han, Jingfeng Zhang

The process involves (i) Locate: concatenating the noise with masked scene image to achieve precise regional editing, (ii) Assign: employing decoupled cross-attention mechanism to accommodate multi-modal guidance, and (iii) Refine: using a novel RefineNet to supplement subject details.

Image Inpainting

Stop Reasoning! When Multimodal LLMs with Chain-of-Thought Reasoning Meets Adversarial Images

no code implementations22 Feb 2024 Zefeng Wang, Zhen Han, Shuo Chen, Fan Xue, Zifeng Ding, Xun Xiao, Volker Tresp, Philip Torr, Jindong Gu

Our research evaluates the adversarial robustness of MLLMs when employing CoT reasoning, finding that CoT marginally improves adversarial robustness against existing attack methods.

Adversarial Robustness

SCEdit: Efficient and Controllable Image Diffusion Generation via Skip Connection Editing

2 code implementations18 Dec 2023 Zeyinzi Jiang, Chaojie Mao, Yulin Pan, Zhen Han, Jingfeng Zhang

Image diffusion models have been utilized in various tasks, such as text-to-image generation and controllable image synthesis.

Decoder Text-to-Image Generation

Understanding and Improving In-Context Learning on Vision-language Models

no code implementations29 Nov 2023 Shuo Chen, Zhen Han, Bailan He, Mark Buckley, Philip Torr, Volker Tresp, Jindong Gu

Our findings indicate that ICL in VLMs is predominantly driven by the textual information in the demonstrations whereas the visual information in the demonstrations barely affects the ICL performance.

In-Context Learning

GraphextQA: A Benchmark for Evaluating Graph-Enhanced Large Language Models

1 code implementation12 Oct 2023 Yuanchun Shen, Ruotong Liao, Zhen Han, Yunpu Ma, Volker Tresp

The proposed dataset is designed to evaluate graph-language models' ability to understand graphs and make use of it for answer generation.

Answer Generation Hallucination +3

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

1 code implementation24 Jul 2023 Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip Torr

This paper aims to provide a comprehensive survey of cutting-edge research in prompt engineering on three types of vision-language models: multimodal-to-text generation models (e. g. Flamingo), image-text matching models (e. g.

Image-text matching Language Modelling +4

Logic Diffusion for Knowledge Graph Reasoning

no code implementations6 Jun 2023 Xiaoying Xie, Biao Gong, Yiliang Lv, Zhen Han, Guoshuai Zhao, Xueming Qian

Most recent works focus on answering first order logical queries to explore the knowledge graph reasoning via multi-hop logic predictions.

A Graph-Guided Reasoning Approach for Open-ended Commonsense Question Answering

no code implementations18 Mar 2023 Zhen Han, Yue Feng, Mingming Sun

Hence, a new benchmark challenge set for open-ended commonsense reasoning (OpenCSR) has been recently released, which contains natural science questions without any predefined choices.

Multiple-choice Question Answering +1

Mutimodal Ranking Optimization for Heterogeneous Face Re-identification

no code implementations11 Dec 2022 Hui Hu, Jiawei Zhang, Zhen Han

Secondly, we propose linear and non-linear fusion strategies to aggregate initial ranking lists of multimodal face pairs and acquire the optimized re-ranked list based on modal complementarity.

Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Information

no code implementations15 Nov 2022 Zifeng Ding, Jingpei Wu, Bailan He, Yunpu Ma, Zhen Han, Volker Tresp

Similar problem exists in temporal knowledge graphs (TKGs), and no previous temporal knowledge graph completion (TKGC) method is developed for modeling newly-emerged entities.

Link Prediction Meta-Learning +1

Deepfake Face Traceability with Disentangling Reversing Network

no code implementations8 Jul 2022 Jiaxin Ai, Zhongyuan Wang, Baojin Huang, Zhen Han

Deepfake face not only violates the privacy of personal identity, but also confuses the public and causes huge social harm.

DeepFake Detection Face Swapping

Continuous Temporal Graph Networks for Event-Based Graph Data

no code implementations NAACL (DLG4NLP) 2022 Jin Guo, Zhen Han, Zhou Su, Jiliang Li, Volker Tresp, Yuyi Wang

Hence, we propose Continuous Temporal Graph Networks (CTGNs) to capture the continuous dynamics of temporal graph data.

Learning Meta Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction

no code implementations21 May 2022 Zifeng Ding, Bailan He, Yunpu Ma, Zhen Han, Volker Tresp

In this paper, we follow the previous work that focuses on few-shot relational learning on static KGs and extend two fundamental TKG reasoning tasks, i. e., interpolated and extrapolated link prediction, to the one-shot setting.

Few-Shot Learning Knowledge Graphs +2

ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations

no code implementations17 Mar 2022 Zhen Han, Ruotong Liao, Jindong Gu, Yao Zhang, Zifeng Ding, Yujia Gu, Heinz Köppl, Hinrich Schütze, Volker Tresp

Since conventional knowledge embedding models cannot take full advantage of the abundant textual information, there have been extensive research efforts in enhancing knowledge embedding using texts.

Knowledge Graph Embedding Link Prediction +1

Consistent Style Transfer

1 code implementation6 Jan 2022 Xuan Luo, Zhen Han, Lingkang Yang, Lingling Zhang

Recently, attentional arbitrary style transfer methods have been proposed to achieve fine-grained results, which manipulates the point-wise similarity between content and style features for stylization.

Style Transfer

TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting

1 code implementation EMNLP 2021 Haohai Sun, Jialun Zhong, Yunpu Ma, Zhen Han, Kun He

Compared with the completion task, the forecasting task is more difficult that faces two main challenges: (1) how to effectively model the time information to handle future timestamps?

Link Prediction reinforcement-learning +1

Video Similarity and Alignment Learning on Partial Video Copy Detection

no code implementations4 Aug 2021 Zhen Han, Xiangteng He, Mingqian Tang, Yiliang Lv

To address the above issues, we propose the Video Similarity and Alignment Learning (VSAL) approach, which jointly models spatial similarity, temporal similarity and partial alignment.

Copy Detection Partial Video Copy Detection +1

When Face Recognition Meets Occlusion: A New Benchmark

1 code implementation4 Mar 2021 Baojin Huang, Zhongyuan Wang, Guangcheng Wang, Kui Jiang, Kangli Zeng, Zhen Han, Xin Tian, Yuhong Yang

In particular, we first collect a variety of glasses and masks as occlusion, and randomly combine the occlusion attributes (occlusion objects, textures, and colors) to achieve a large number of more realistic occlusion types.

Face Recognition

Temporal Knowledge Graph Forecasting with Neural ODE

1 code implementation13 Jan 2021 Zhen Han, Zifeng Ding, Yunpu Ma, Yujia Gu, Volker Tresp

In addition, a novel graph transition layer is applied to capture the transitions on the dynamic graph, i. e., edge formation and dissolution.

Future prediction Knowledge Graphs

Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs

1 code implementation AKBC 2020 Zhen Han, Yunpu Ma, Yuyi Wang, Stephan Günnemann, Volker Tresp

The Hawkes process has become a standard method for modeling self-exciting event sequences with different event types.

Knowledge Graphs

MMD GAN with Random-Forest Kernels

no code implementations ICLR 2020 Tao Huang, Zhen Han, Xu Jia, Hanyuan Hang

In this paper, we propose a novel kind of kernel, random forest kernel, to enhance the empirical performance of MMD GAN.

Ensemble Learning

Unsupervised Image Super-Resolution with an Indirect Supervised Path

no code implementations7 Oct 2019 Zhen Han, Enyan Dai, Xu Jia, Xiaoying Ren, Shuaijun Chen, Chunjing Xu, Jianzhuang Liu, Qi Tian

The task of single image super-resolution (SISR) aims at reconstructing a high-resolution (HR) image from a low-resolution (LR) image.

Image Super-Resolution Translation

Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate

no code implementations1 Aug 2018 Sheng Chen, Jia Guo, Yang Liu, Xiang Gao, Zhen Han

In this paper, we propose a novel Global Norm-Aware Pooling (GNAP) block, which reweights local features in a convolutional neural network (CNN) adaptively according to their L2 norms and outputs a global feature vector with a global average pooling layer.

Face Recognition Robust Face Recognition

Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding

no code implementations18 Jul 2018 Tong Chen, Wenjia Niu, Yingxiao Xiang, Xiaoxuan Bai, Jiqiang Liu, Zhen Han, Gang Li

In addition, we propose Gradient Band-based Adversarial Training, which trained with a single randomly choose dominant adversarial example without taking any modification, to realize the "1:N" attack immunity for generalized dominant adversarial examples.

Dynamic Stacked Generalization for Node Classification on Networks

no code implementations16 Oct 2016 Zhen Han, Alyson Wilson

We propose a novel stacked generalization (stacking) method as a dynamic ensemble technique using a pool of heterogeneous classifiers for node label classification on networks.

Classification General Classification +1

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