Search Results for author: Qi Cao

Found 33 papers, 20 papers with code

When to Trust LLMs: Aligning Confidence with Response Quality

no code implementations26 Apr 2024 Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, HuaWei Shen, Bolin Ding

Specifically, the order-preserving reward incentivizes the model to verbalize greater confidence for responses of higher quality to align the order of confidence and quality.

Text Generation

LoRec: Large Language Model for Robust Sequential Recommendation against Poisoning Attacks

no code implementations31 Jan 2024 Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, HuaWei Shen, Xueqi Cheng

Traditional defense strategies predominantly depend on predefined assumptions or rules extracted from specific known attacks, limiting their generalizability to unknown attack types.

Language Modelling Large Language Model +2

Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts for Open-Domain QA?

no code implementations22 Jan 2024 Hexiang Tan, Fei Sun, Wanli Yang, Yuanzhuo Wang, Qi Cao, Xueqi Cheng

While auxiliary information has become a key to enhancing Large Language Models (LLMs), relatively little is known about how LLMs merge these contexts, specifically contexts generated by LLMs and those retrieved from external sources.

FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement

1 code implementation20 Jan 2024 Dezhong Yao, Tongtong Liu, Qi Cao, Hai Jin

Federated Learning (FL) has emerged as a promising approach for preserving data privacy in recommendation systems by training models locally.

Federated Learning Privacy Preserving +1

Fine-Tuning InstructPix2Pix for Advanced Image Colorization

1 code implementation8 Dec 2023 Zifeng An, Zijing Xu, Eric Fan, Qi Cao

This paper presents a novel approach to human image colorization by fine-tuning the InstructPix2Pix model, which integrates a language model (GPT-3) with a text-to-image model (Stable Diffusion).

Colorization Image Colorization +1

Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text

1 code implementation30 Nov 2023 Qi Cao, Takeshi Kojima, Yutaka Matsuo, Yusuke Iwasawa

While Large Language Models (LLMs) have achieved remarkable performance in many tasks, much about their inner workings remains unclear.

Robust Recommender System: A Survey and Future Directions

no code implementations5 Sep 2023 Kaike Zhang, Qi Cao, Fei Sun, Yunfan Wu, Shuchang Tao, HuaWei Shen, Xueqi Cheng

With the rapid growth of information, recommender systems have become integral for providing personalized suggestions and overcoming information overload.

Fairness Recommendation Systems +1

AutoHint: Automatic Prompt Optimization with Hint Generation

1 code implementation13 Jul 2023 Hong Sun, Xue Li, Yinchuan Xu, Youkow Homma, Qi Cao, Min Wu, Jian Jiao, Denis Charles

This paper presents AutoHint, a novel framework for automatic prompt engineering and optimization for Large Language Models (LLM).

Hint Generation In-Context Learning +2

IDEA: Invariant Defense for Graph Adversarial Robustness

no code implementations25 May 2023 Shuchang Tao, Qi Cao, HuaWei Shen, Yunfan Wu, Bingbing Xu, Xueqi Cheng

To address these limitations, we analyze the causalities in graph adversarial attacks and conclude that causal features are key to achieve graph adversarial robustness, owing to their determinedness for labels and invariance across attacks.

Adversarial Robustness

Popularity Debiasing from Exposure to Interaction in Collaborative Filtering

1 code implementation9 May 2023 YuanHao Liu, Qi Cao, HuaWei Shen, Yunfan Wu, Shuchang Tao, Xueqi Cheng

In this paper, we propose a new criterion for popularity debiasing, i. e., in an unbiased recommender system, both popular and unpopular items should receive Interactions Proportional to the number of users who Like it, namely IPL criterion.

Collaborative Filtering Recommendation Systems

Graph Adversarial Immunization for Certifiable Robustness

1 code implementation16 Feb 2023 Shuchang Tao, HuaWei Shen, Qi Cao, Yunfan Wu, Liang Hou, Xueqi Cheng

In this paper, we propose and formulate graph adversarial immunization, i. e., vaccinating part of graph structure to improve certifiable robustness of graph against any admissible adversarial attack.

Adversarial Attack Combinatorial Optimization

Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation

1 code implementation5 Feb 2023 JunJie Huang, Qi Cao, Ruobing Xie, Shaoliang Zhang, Feng Xia, HuaWei Shen, Xueqi Cheng

To reduce the influence of data sparsity, Graph Contrastive Learning (GCL) is adopted in GNN-based CF methods for enhancing performance.

Contrastive Learning Data Augmentation

Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective

no code implementations20 Nov 2022 Yige Yuan, Bingbing Xu, HuaWei Shen, Qi Cao, Keting Cen, Wen Zheng, Xueqi Cheng

Guided by the bound, we design a GCL framework named InfoAdv with enhanced generalization ability, which jointly optimizes the generalization metric and InfoMax to strike the right balance between pretext task fitting and the generalization ability on downstream tasks.

Contrastive Learning Data Augmentation +1

Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network

no code implementations16 Nov 2022 Yang Li, Bingbing Xu, Qi Cao, Yige Yuan, HuaWei Shen

On account that previous studies either lacks variance analysis or only focus on a particular sampling paradigm, we firstly propose an unified node sampling variance analysis framework and analyze the core challenge "circular dependency" for deriving the minimum variance sampler, i. e., sampling probability depends on node embeddings while node embeddings can not be calculated until sampling is finished.

Time Series Time Series Analysis

Adversarial Camouflage for Node Injection Attack on Graphs

1 code implementation3 Aug 2022 Shuchang Tao, Qi Cao, HuaWei Shen, Yunfan Wu, Liang Hou, Fei Sun, Xueqi Cheng

In this paper, we first propose and define camouflage as distribution similarity between ego networks of injected nodes and normal nodes.

Single Node Injection Attack against Graph Neural Networks

1 code implementation30 Aug 2021 Shuchang Tao, Qi Cao, HuaWei Shen, JunJie Huang, Yunfan Wu, Xueqi Cheng

In this paper, we focus on an extremely limited scenario of single node injection evasion attack, i. e., the attacker is only allowed to inject one single node during the test phase to hurt GNN's performance.

Signed Bipartite Graph Neural Networks

1 code implementation22 Aug 2021 JunJie Huang, HuaWei Shen, Qi Cao, Shuchang Tao, Xueqi Cheng

Signed bipartite networks are different from classical signed networks, which contain two different node sets and signed links between two node sets.

Link Sign Prediction Network Embedding

Conditional GANs with Auxiliary Discriminative Classifier

2 code implementations21 Jul 2021 Liang Hou, Qi Cao, HuaWei Shen, Siyuan Pan, Xiaoshuang Li, Xueqi Cheng

Specifically, the proposed auxiliary discriminative classifier becomes generator-aware by recognizing the class-labels of the real data and the generated data discriminatively.

Conditional Image Generation Generative Adversarial Network

INMO: A Model-Agnostic and Scalable Module for Inductive Collaborative Filtering

1 code implementation12 Jul 2021 Yunfan Wu, Qi Cao, HuaWei Shen, Shuchang Tao, Xueqi Cheng

INMO generates the inductive embeddings for users (items) by characterizing their interactions with some template items (template users), instead of employing an embedding lookup table.

Collaborative Filtering Recommendation Systems

Self-Supervised GANs with Label Augmentation

2 code implementations NeurIPS 2021 Liang Hou, HuaWei Shen, Qi Cao, Xueqi Cheng

Recently, transformation-based self-supervised learning has been applied to generative adversarial networks (GANs) to mitigate catastrophic forgetting in the discriminator by introducing a stationary learning environment.

Data Augmentation Image Generation +2

A Non-sequential Approach to Deep User Interest Model for CTR Prediction

no code implementations5 Apr 2021 Keke Zhao, Xing Zhao, Qi Cao, Linjian Mo

The framework can partition data into custom designed time buckets to capture the interactions among information aggregated in different time buckets.

Click-Through Rate Prediction

Towards Powerful Graph Neural Networks: Diversity Matters

no code implementations1 Jan 2021 Xu Bingbing, HuaWei Shen, Qi Cao, YuanHao Liu, Keting Cen, Xueqi Cheng

For a target node, diverse sampling offers it diverse neighborhoods, i. e., rooted sub-graphs, and the representation of target node is finally obtained via aggregating the representation of diverse neighborhoods obtained using any GNN model.

Graph Representation Learning Node Classification

Fairness-Oriented User Scheduling for Bursty Downlink Transmission Using Multi-Agent Reinforcement Learning

no code implementations30 Dec 2020 Mingqi Yuan, Qi Cao, Man-on Pun, Yi Chen

In this work, we develop practical user scheduling algorithms for downlink bursty traffic with emphasis on user fairness.

Distributed Optimization Fairness +3

Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning

1 code implementation27 Jul 2020 Bingbing Xu, Hua-Wei Shen, Qi Cao, Keting Cen, Xue-Qi Cheng

Graph convolutional networks gain remarkable success in semi-supervised learning on graph structured data.

Adversarial Immunization for Certifiable Robustness on Graphs

2 code implementations19 Jul 2020 Shuchang Tao, Hua-Wei Shen, Qi Cao, Liang Hou, Xue-Qi Cheng

Despite achieving strong performance in semi-supervised node classification task, graph neural networks (GNNs) are vulnerable to adversarial attacks, similar to other deep learning models.

Adversarial Attack Bilevel Optimization +2

IllumiNet: Transferring Illumination from Planar Surfaces to Virtual Objects in Augmented Reality

no code implementations12 Jul 2020 Di Xu, Zhen Li, Yanning Zhang, Qi Cao

This paper presents an illumination estimation method for virtual objects in real environment by learning.

Popularity Prediction on Social Platforms with Coupled Graph Neural Networks

1 code implementation21 Jun 2019 Qi Cao, Hua-Wei Shen, Jinhua Gao, Bingzheng Wei, Xue-Qi Cheng

In this paper, we consider the problem of network-aware popularity prediction, leveraging both early adopters and social networks for popularity prediction.

ANAE: Learning Node Context Representation for Attributed Network Embedding

no code implementations20 Jun 2019 Keting Cen, Hua-Wei Shen, Jinhua Gao, Qi Cao, Bingbing Xu, Xue-Qi Cheng

In this paper, we address attributed network embedding from a novel perspective, i. e., learning node context representation for each node via modeling its attributed local subgraph.

Attribute Decoder +4

Graph Wavelet Neural Network

1 code implementation ICLR 2019 Bingbing Xu, Hua-Wei Shen, Qi Cao, Yunqi Qiu, Xue-Qi Cheng

We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform.

General Classification

DeepHawkes: Bridging the gap between prediction and understanding of information cascades

1 code implementation CIKM 2017 Qi Cao, HuaWei Shen, Keting Cen, Wentao Ouyang, Xueqi Cheng

In this paper, we propose DeepHawkes to combat the defects of existing methods, leveraging end-to-end deep learning to make an analogy to interpretable factors of Hawkes process — a widely-used generative process to model information cascade.

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