Search Results for author: Yifei Zhang

Found 70 papers, 26 papers with code

A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation

no code implementations14 Jun 2024 Yongkang Liu, Ercong Nie, Zheng Hua, Zifeng Ding, Daling Wang, Yifei Zhang, Hinrich Schütze

We conduct experiments on Chinese dialogue datasets from five different domains and show that AMD$^2$G achieves superior performance compared to both direct training on the target domain corpus and collective training on all five domain corpora.

Neuroscheduling for Remote Estimation

no code implementations17 May 2024 Marcos M. Vasconcelos, Yifei Zhang

Many modern distributed systems consist of devices that generate more data than what can be transmitted via a communication link in near real time with high-fidelity.

Scheduling

On Joint Marginal Expected Shortfall and Associated Contribution Risk Measures

no code implementations13 May 2024 Tong Pu, Yifei Zhang, Yiying Zhang

Various systemic risk measures have been proposed in the literature to quantify the domino and (relative) spillover effects induced by systemic risks such as the well-known CoVaR, CoES, MES and CoD risk measures, and associated contribution measures.

Spectrally Pruned Gaussian Fields with Neural Compensation

1 code implementation1 May 2024 Runyi Yang, Zhenxin Zhu, Zhou Jiang, Baijun Ye, Xiaoxue Chen, Yifei Zhang, Yuantao Chen, Jian Zhao, Hao Zhao

However, this comes with high memory consumption, e. g., a well-trained Gaussian field may utilize three million Gaussian primitives and over 700 MB of memory.

DreamLIP: Language-Image Pre-training with Long Captions

1 code implementation25 Mar 2024 Kecheng Zheng, Yifei Zhang, Wei Wu, Fan Lu, Shuailei Ma, Xin Jin, Wei Chen, Yujun Shen

Motivated by this, we propose to dynamically sample sub-captions from the text label to construct multiple positive pairs, and introduce a grouping loss to match the embeddings of each sub-caption with its corresponding local image patches in a self-supervised manner.

Contrastive Learning Language Modelling +4

FlashFace: Human Image Personalization with High-fidelity Identity Preservation

no code implementations25 Mar 2024 Shilong Zhang, Lianghua Huang, Xi Chen, Yifei Zhang, Zhi-Fan Wu, Yutong Feng, Wei Wang, Yujun Shen, Yu Liu, Ping Luo

This work presents FlashFace, a practical tool with which users can easily personalize their own photos on the fly by providing one or a few reference face images and a text prompt.

Face Swapping Instruction Following +1

Is Mamba Effective for Time Series Forecasting?

1 code implementation17 Mar 2024 Zihan Wang, Fanheng Kong, Shi Feng, Ming Wang, Xiaocui Yang, Han Zhao, Daling Wang, Yifei Zhang

For TSF tasks, these characteristics enable Mamba to comprehend hidden patterns as the Transformer and reduce computational overhead compared to the Transformer.

Computational Efficiency Time Series +1

DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation

no code implementations16 Mar 2024 Qilong Zhao, Yifei Zhang, Mengdan Zhu, Siyi Gu, Yuyang Gao, Xiaofeng Yang, Liang Zhao

Explanation supervision aims to enhance deep learning models by integrating additional signals to guide the generation of model explanations, showcasing notable improvements in both the predictability and explainability of the model.

Imputation

ELAD: Explanation-Guided Large Language Models Active Distillation

no code implementations20 Feb 2024 Yifei Zhang, Bo Pan, Chen Ling, Yuntong Hu, Liang Zhao

The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences.

Active Learning Knowledge Distillation

Distilling Large Language Models for Text-Attributed Graph Learning

no code implementations19 Feb 2024 Bo Pan, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao

To address the inherent gaps between LLMs (generative models for texts) and graph models (discriminative models for graphs), we propose first to let LLMs teach an interpreter with rich textual rationale and then let a student model mimic the interpreter's reasoning without LLMs' textual rationale.

Graph Learning TAG

HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy

1 code implementation26 Jan 2024 Yongkang Liu, Yiqun Zhang, Qian Li, Tong Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze

As LMs grow in size, fine-tuning the full parameters of LMs requires a prohibitively large amount of GPU memory.

STICKERCONV: Generating Multimodal Empathetic Responses from Scratch

1 code implementation20 Jan 2024 Yiqun Zhang, Fanheng Kong, Peidong Wang, Shuang Sun, Lingshuai Wang, Shi Feng, Daling Wang, Yifei Zhang, Kaisong Song

Stickers, while widely recognized for enhancing empathetic communication in online interactions, remain underexplored in current empathetic dialogue research, notably due to the challenge of a lack of comprehensive datasets.

2k Empathetic Response Generation +1

CodePrompt: Improving Source Code-Related Classification with Knowledge Features through Prompt Learning

no code implementations10 Jan 2024 Yong Ma, Senlin Luo, Yu-Ming Shang, Yifei Zhang, ZhengJun Li

Researchers have explored the potential of utilizing pre-trained language models, such as CodeBERT, to improve source code-related tasks.

Language Modelling Sentence +2

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models

1 code implementation1 Jan 2024 Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao

We categorize methods based on their optimization focus: computational, memory, energy, financial, and network resources and their applicability across various stages of an LLM's lifecycle, including architecture design, pretraining, finetuning, and system design.

Alignment and Outer Shell Isotropy for Hyperbolic Graph Contrastive Learning

no code implementations27 Oct 2023 Yifei Zhang, Hao Zhu, Jiahong Liu, Piotr Koniusz, Irwin King

We show that in the hyperbolic space one has to address the leaf- and height-level uniformity which are related to properties of trees, whereas in the ambient space of the hyperbolic manifold, these notions translate into imposing an isotropic ring density towards boundaries of Poincar\'e ball.

Contrastive Learning Graph Embedding +1

MM-BigBench: Evaluating Multimodal Models on Multimodal Content Comprehension Tasks

2 code implementations13 Oct 2023 Xiaocui Yang, Wenfang Wu, Shi Feng, Ming Wang, Daling Wang, Yang Li, Qi Sun, Yifei Zhang, XiaoMing Fu, Soujanya Poria

Consequently, our work complements research on the performance of MLLMs in multimodal comprehension tasks, achieving a more comprehensive and holistic evaluation of MLLMs.

Multimodal Reasoning

Visual Attention Prompted Prediction and Learning

1 code implementation12 Oct 2023 Yifei Zhang, Siyi Gu, Bo Pan, Guangji Bai, Meikang Qiu, Xiaofeng Yang, Liang Zhao

However, in many real-world situations, it is usually desired to prompt the model with visual attention without model retraining.

Decision Making

XAI Benchmark for Visual Explanation

no code implementations12 Oct 2023 Yifei Zhang, Siyi Gu, James Song, Bo Pan, Guangji Bai, Liang Zhao

Our proposed benchmarks facilitate a fair evaluation and comparison of visual explanation methods.

Decision Making Explainable artificial intelligence +2

Controllable Data Generation Via Iterative Data-Property Mutual Mappings

no code implementations11 Oct 2023 Bo Pan, Muran Qin, Shiyu Wang, Yifei Zhang, Liang Zhao

To address these challenges, in this paper, we propose a general framework to enhance VAE-based data generators with property controllability and ensure disentanglement.

Disentanglement

SurroCBM: Concept Bottleneck Surrogate Models for Generative Post-hoc Explanation

no code implementations11 Oct 2023 Bo Pan, Zhenke Liu, Yifei Zhang, Liang Zhao

Explainable AI seeks to bring light to the decision-making processes of black-box models.

Decision Making

Saliency-Guided Hidden Associative Replay for Continual Learning

1 code implementation6 Oct 2023 Guangji Bai, Qilong Zhao, Xiaoyang Jiang, Yifei Zhang, Liang Zhao

Continual Learning is a burgeoning domain in next-generation AI, focusing on training neural networks over a sequence of tasks akin to human learning.

Continual Learning Retrieval

Multi-Prompt Fine-Tuning of Foundation Models for Enhanced Medical Image Segmentation

no code implementations3 Oct 2023 Xiangru Li, Yifei Zhang, Liang Zhao

The Segment Anything Model (SAM) is a powerful foundation model that introduced revolutionary advancements in natural image segmentation.

Decoder Image Segmentation +3

Rationality and connectivity in stochastic learning for networked coordination games

no code implementations29 Sep 2023 Yifei Zhang, Marcos M. Vasconcelos

Our analysis shows that there is a relationship between the connectivity of the network, and the rationality of the agents.

Large Language Models Are Also Good Prototypical Commonsense Reasoners

no code implementations22 Sep 2023 Chenin Li, Qianglong Chen, Yin Zhang, Yifei Zhang, Hongxiang Yao

Commonsense reasoning is a pivotal skill for large language models, yet it presents persistent challenges in specific tasks requiring this competence.

StrategyQA

Eliminating Lipschitz Singularities in Diffusion Models

no code implementations20 Jun 2023 Zhantao Yang, Ruili Feng, Han Zhang, Yujun Shen, Kai Zhu, Lianghua Huang, Yifei Zhang, Yu Liu, Deli Zhao, Jingren Zhou, Fan Cheng

Diffusion models, which employ stochastic differential equations to sample images through integrals, have emerged as a dominant class of generative models.

InRank: Incremental Low-Rank Learning

1 code implementation20 Jun 2023 Jiawei Zhao, Yifei Zhang, Beidi Chen, Florian Schäfer, Anima Anandkumar

To remedy this, we design a new training algorithm Incremental Low-Rank Learning (InRank), which explicitly expresses cumulative weight updates as low-rank matrices while incrementally augmenting their ranks during training.

Computational Efficiency

Cones 2: Customizable Image Synthesis with Multiple Subjects

1 code implementation30 May 2023 Zhiheng Liu, Yifei Zhang, Yujun Shen, Kecheng Zheng, Kai Zhu, Ruili Feng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao

Synthesizing images with user-specified subjects has received growing attention due to its practical applications.

Image Generation

Evaluate What You Can't Evaluate: Unassessable Quality for Generated Response

no code implementations24 May 2023 Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze

There are risks in using eference-free evaluators based on LLMs to evaluate the quality of dialogue responses.

Dialogue Generation

Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space

no code implementations1 Apr 2023 Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King

We propose an end-to-end Bipartite Graph Convolutional Hashing approach, namely BGCH, which consists of three novel and effective modules: (1) adaptive graph convolutional hashing, (2) latent feature dispersion, and (3) Fourier serialized gradient estimation.

Retrieval

Cones: Concept Neurons in Diffusion Models for Customized Generation

1 code implementation9 Mar 2023 Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, Yang Cao

Concatenating multiple clusters of concept neurons can vividly generate all related concepts in a single image.

oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

no code implementations3 Jan 2023 Jianhui Li, Zhennan Qin, Yijie Mei, Jingze Cui, Yunfei Song, Ciyong Chen, Yifei Zhang, Longsheng Du, Xianhang Cheng, Baihui Jin, Yan Zhang, Jason Ye, Eric Lin, Dan Lavery

We present oneDNN Graph Compiler, a tensor compiler that employs a hybrid approach of using techniques from both compiler optimization and expert-tuned kernels for high performance code generation of the deep neural network graph.

Code Generation Compiler Optimization

MAGI: Multi-Annotated Explanation-Guided Learning

no code implementations ICCV 2023 Yifei Zhang, Siyi Gu, Yuyang Gao, Bo Pan, Xiaofeng Yang, Liang Zhao

This technique aims to improve the predictability of the model by incorporating human understanding of the prediction process into the training phase.

Variational Inference

Learning to Select Prototypical Parts for Interpretable Sequential Data Modeling

1 code implementation7 Dec 2022 Yifei Zhang, Neng Gao, Cunqing Ma

Prototype-based interpretability methods provide intuitive explanations of model prediction by comparing samples to a reference set of memorized exemplars or typical representatives in terms of similarity.

Spectral Feature Augmentation for Graph Contrastive Learning and Beyond

no code implementations2 Dec 2022 Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

Although augmentations (e. g., perturbation of graph edges, image crops) boost the efficiency of Contrastive Learning (CL), feature level augmentation is another plausible, complementary yet not well researched strategy.

Contrastive Learning

Sample Complexity for Evaluating the Robust Linear Observers Performance under Coprime Factors Uncertainty

no code implementations29 Nov 2022 Yifei Zhang, Sourav Kumar Ukil, Andrei Sperila, Serban Sabau

Refitting the expression of the relevant closed loop allows for the optimal linear observer problem given a fixed state feedback gain to be recast as a convex problem in the Youla parameter.

Time Series Time Series Analysis

Dimensionality-Varying Diffusion Process

no code implementations CVPR 2023 Han Zhang, Ruili Feng, Zhantao Yang, Lianghua Huang, Yu Liu, Yifei Zhang, Yujun Shen, Deli Zhao, Jingren Zhou, Fan Cheng

Diffusion models, which learn to reverse a signal destruction process to generate new data, typically require the signal at each step to have the same dimension.

Image Generation

Alleviating Sparsity of Open Knowledge Graphs with Ternary Contrastive Learning

1 code implementation8 Nov 2022 Qian Li, Shafiq Joty, Daling Wang, Shi Feng, Yifei Zhang

Sparsity of formal knowledge and roughness of non-ontological construction make sparsity problem particularly prominent in Open Knowledge Graphs (OpenKGs).

Contrastive Learning Knowledge Graphs +1

Beyond Instance Discrimination: Relation-aware Contrastive Self-supervised Learning

no code implementations2 Nov 2022 Yifei Zhang, Chang Liu, Yu Zhou, Weiping Wang, Qixiang Ye, Xiangyang Ji

In this paper, we present relation-aware contrastive self-supervised learning (ReCo) to integrate instance relations, i. e., global distribution relation and local interpolation relation, into the CSL framework in a plug-and-play fashion.

Relation Self-Supervised Learning

DialogConv: A Lightweight Fully Convolutional Network for Multi-view Response Selection

no code implementations25 Oct 2022 Yongkang Liu, Shi Feng, Wei Gao, Daling Wang, Yifei Zhang

Current end-to-end retrieval-based dialogue systems are mainly based on Recurrent Neural Networks or Transformers with attention mechanisms.

Retrieval

MulZDG: Multilingual Code-Switching Framework for Zero-shot Dialogue Generation

1 code implementation COLING 2022 Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang

Building dialogue generation systems in a zero-shot scenario remains a huge challenge, since the typical zero-shot approaches in dialogue generation rely heavily on large-scale pre-trained language generation models such as GPT-3 and T5.

Data Augmentation Dialogue Generation

Graph Component Contrastive Learning for Concept Relatedness Estimation

1 code implementation25 Jun 2022 Yueen Ma, Zixing Song, Xuming Hu, Jingjing Li, Yifei Zhang, Irwin King

As it is intractable for data augmentation to fully capture the structural information of the ConcreteGraph due to a large amount of potential concept pairs, we further introduce a novel Graph Component Contrastive Learning framework to implicitly learn the complete structure of the ConcreteGraph.

Contrastive Learning Data Augmentation +2

COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning

1 code implementation9 Jun 2022 Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King

In this paper, we show that the node embedding obtained via the graph augmentations is highly biased, somewhat limiting contrastive models from learning discriminative features for downstream tasks.

Contrastive Learning Graph Representation Learning

Graph-adaptive Rectified Linear Unit for Graph Neural Networks

no code implementations13 Feb 2022 Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King

However, in the updating stage, all nodes share the same updating function.

Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty

no code implementations29 Sep 2021 Yifei Zhang, Sourav Kumar Ukil, Ephraim Neimand, Serban Sabau, Myron E. Hohil

The robust LQG synthesis procedure is performed by considering bounded additive model uncertainty on the coprime factors of the plant.

Time Series Time Series Analysis

Dense Semantic Contrast for Self-Supervised Visual Representation Learning

no code implementations16 Sep 2021 Xiaoni Li, Yu Zhou, Yifei Zhang, Aoting Zhang, Wei Wang, Ning Jiang, Haiying Wu, Weiping Wang

Concretely, these downstream tasks require more accurate representation, in other words, the pixels from the same object must belong to a shared semantic category, which is lacking in the previous methods.

Contrastive Learning Instance Segmentation +4

Multimodal Sentiment Detection Based on Multi-channel Graph Neural Networks

1 code implementation ACL 2021 Xiaocui Yang, Shi Feng, Yifei Zhang, Daling Wang

In this paper, we propose Multi-channel Graph Neural Networks with Sentiment-awareness (MGNNS) for image-text sentiment detection.

Exploring Instance Relations for Unsupervised Feature Embedding

1 code implementation7 May 2021 Yifei Zhang, Yu Zhou, Weiping Wang

Despite the great progress achieved in unsupervised feature embedding, existing contrastive learning methods typically pursue view-invariant representations through attracting positive sample pairs and repelling negative sample pairs in the embedding space, while neglecting to systematically explore instance relations.

Contrastive Learning Image Classification +2

Additively Homomorphical Encryption based Deep Neural Network for Asymmetrically Collaborative Machine Learning

no code implementations14 Jul 2020 Yifei Zhang, Hao Zhu

For this scheme, we propose a novel privacy-preserving architecture where two parties can collaboratively train a deep learning model efficiently while preserving the privacy of each party's data.

BIG-bench Machine Learning Privacy Preserving

Progressive Cluster Purification for Unsupervised Feature Learning

1 code implementation6 Jul 2020 Yifei Zhang, Chang Liu, Yu Zhou, Wei Wang, Weiping Wang, Qixiang Ye

In this work, we propose a novel clustering based method, which, by iteratively excluding class inconsistent samples during progressive cluster formation, alleviates the impact of noise samples in a simple-yet-effective manner.

Clustering Specificity

Adversarial Synthesis of Human Pose from Text

no code implementations1 May 2020 Yifei Zhang, Rania Briq, Julian Tanke, Juergen Gall

This work focuses on synthesizing human poses from human-level text descriptions.

Generative Adversarial Network

Answer-Supervised Question Reformulation for Enhancing Conversational Machine Comprehension

no code implementations WS 2019 Qian Li, Hui Su, Cheng Niu, Daling Wang, Zekang Li, Shi Feng, Yifei Zhang

Moreover, pretraining is essential in reinforcement learning models, so we provide a high-quality annotated dataset for question reformulation by sampling a part of QuAC dataset.

Reading Comprehension reinforcement-learning +2

Doc2hash: Learning Discrete Latent variables for Documents Retrieval

1 code implementation NAACL 2019 Yifei Zhang, Hao Zhu

However, the discrete stochastic layer is usually incompatible with the backpropagation in the training stage, and thus causes a gradient flow problem because of non-differentiable operators.

Retrieval

Personalized Microblog Sentiment Classification via Adversarial Cross-lingual Multi-task Learning

no code implementations EMNLP 2018 Weichao Wang, Shi Feng, Wei Gao, Daling Wang, Yifei Zhang

Then the attention-based CNN model is incorporated into a novel adversarial cross-lingual learning framework, in which with the help of user properties as bridge between languages, we can extract the language-specific features and language-independent features to enrich the user post representation so as to alleviate the data insufficiency problem.

General Classification Multi-Task Learning +2

#DebateNight: The Role and Influence of Socialbots on Twitter During the 1st 2016 U.S. Presidential Debate

2 code implementations27 Feb 2018 Marian-Andrei Rizoiu, Timothy Graham, Rui Zhang, Yifei Zhang, Robert Ackland, Lexing Xie

We collect a large dataset of tweets during the 1st U. S. Presidential Debate in 2016 (#DebateNight) and we analyze its 1. 5 million users from three perspectives: user influence, political behavior (partisanship and engagement) and botness.

Social and Information Networks

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