Search Results for author: Zhiwei Liu

Found 78 papers, 43 papers with code

Instruction-based Hypergraph Pretraining

no code implementations28 Mar 2024 Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

However, the gap between training objectives and the discrepancy between data distributions in pretraining and downstream tasks hinders the transfer of the pretrained knowledge.

Graph Learning Link Prediction +1

MetaAligner: Conditional Weak-to-Strong Correction for Generalizable Multi-Objective Alignment of Language Models

no code implementations25 Mar 2024 Kailai Yang, Zhiwei Liu, Qianqian Xie, Tianlin Zhang, Nirui Song, Jimin Huang, Ziyan Kuang, Sophia Ananiadou

Recent advancements in large language models (LLMs) aim to tackle heterogeneous human expectations and values via multi-objective preference alignment.

In-Context Learning

E4C: Enhance Editability for Text-Based Image Editing by Harnessing Efficient CLIP Guidance

no code implementations15 Mar 2024 Tianrui Huang, Pu Cao, Lu Yang, Chun Liu, Mengjie Hu, Zhiwei Liu, Qing Song

Diffusion-based image editing is a composite process of preserving the source image content and generating new content or applying modifications.

Text-based Image Editing

ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model

1 code implementation11 Mar 2024 Zhiwei Liu, Boyang Liu, Paul Thompson, Kailai Yang, Raghav Jain, Sophia Ananiadou

Driven by a comprehensive analysis of conspiracy text that reveals its distinctive affective features, we propose ConspEmoLLM, the first open-source LLM that integrates affective information and is able to perform diverse tasks relating to conspiracy theories.

Binary Classification Language Modelling +2

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning

2 code implementations23 Feb 2024 JianGuo Zhang, Tian Lan, Rithesh Murthy, Zhiwei Liu, Weiran Yao, Juntao Tan, Thai Hoang, Liangwei Yang, Yihao Feng, Zuxin Liu, Tulika Awalgaonkar, Juan Carlos Niebles, Silvio Savarese, Shelby Heinecke, Huan Wang, Caiming Xiong

It meticulously standardizes and unifies these trajectories into a consistent format, streamlining the creation of a generic data loader optimized for agent training.

AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System

1 code implementation23 Feb 2024 Zhiwei Liu, Weiran Yao, JianGuo Zhang, Liangwei Yang, Zuxin Liu, Juntao Tan, Prafulla K. Choubey, Tian Lan, Jason Wu, Huan Wang, Shelby Heinecke, Caiming Xiong, Silvio Savarese

Thus, we open-source a new AI agent library, AgentLite, which simplifies this process by offering a lightweight, user-friendly platform for innovating LLM agent reasoning, architectures, and applications with ease.

AFPR-CIM: An Analog-Domain Floating-Point RRAM-based Compute-In-Memory Architecture with Dynamic Range Adaptive FP-ADC

no code implementations21 Feb 2024 Haobo Liu, Zhengyang Qian, Wei Wu, Hongwei Ren, Zhiwei Liu, Leibin Ni

Moreover, a novel FP-DAC is also implemented which reconstructs FP digital codes into analog values to perform analog computation.

PFDM: Parser-Free Virtual Try-on via Diffusion Model

no code implementations5 Feb 2024 Yunfang Niu, Dong Yi, Lingxiang Wu, Zhiwei Liu, Pengxiang Cai, Jinqiao Wang

Virtual try-on can significantly improve the garment shopping experiences in both online and in-store scenarios, attracting broad interest in computer vision.

Virtual Try-on

Code-Based English Models Surprising Performance on Chinese QA Pair Extraction Task

no code implementations16 Jan 2024 Linghan Zheng, Hui Liu, Xiaojun Lin, Jiayuan Dong, Yue Sheng, Gang Shi, Zhiwei Liu, Hongwei Chen

In previous studies, code-based models have consistently outperformed text-based models in reasoning-intensive scenarios.


EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis

1 code implementation16 Jan 2024 Zhiwei Liu, Kailai Yang, Tianlin Zhang, Qianqian Xie, Zeping Yu, Sophia Ananiadou

In this paper, we propose EmoLLMs, the first series of open-sourced instruction-following LLMs for comprehensive affective analysis based on fine-tuning various LLMs with instruction data, the first multi-task affective analysis instruction dataset (AAID) with 234K data samples based on various classification and regression tasks to support LLM instruction tuning, and a comprehensive affective evaluation benchmark (AEB) with 14 tasks from various sources and domains to test the generalization ability of LLMs.

Instruction Following regression +1

Semi-Supervised Clustering via Structural Entropy with Different Constraints

1 code implementation18 Dec 2023 Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He

In this work, we present Semi-supervised clustering via Structural Entropy (SSE), a novel method that can incorporate different types of constraints from diverse sources to perform both partitioning and hierarchical clustering.


DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation

no code implementations18 Dec 2023 Yu Wang, Zhiwei Liu, JianGuo Zhang, Weiran Yao, Shelby Heinecke, Philip S. Yu

With our principle, we managed to outperform GPT-Turbo-3. 5 on three datasets using 7b models e. g., Vicuna-7b and Openchat-7b on NDCG@10.

In-Context Learning Sequential Recommendation

Multi-view Graph Convolution for Participant Recommendation

no code implementations20 Nov 2023 Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu

Participant recommendation, a fundamental problem emerging together with GB, aims to find the participants for a launched group buying process with an initiator and a target item to increase the GB success rate.

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation

1 code implementation16 Nov 2023 Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu

The users' group participation on social platforms reveals their interests and can be utilized as side information to mitigate the data sparsity and cold-start problem in recommender systems.

Informativeness Recommendation Systems

Emotion Detection for Misinformation: A Review

no code implementations1 Nov 2023 Zhiwei Liu, Tianlin Zhang, Kailai Yang, Paul Thompson, Zeping Yu, Sophia Ananiadou

The emotions and sentiments of netizens, as expressed in social media posts and news, constitute important factors that can help to distinguish fake news from genuine news and to understand the spread of rumors.

Fake News Detection Misinformation

Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection

1 code implementation30 Oct 2023 Jiaqian Ren, Hao Peng, Lei Jiang, Zhiwei Liu, Jia Wu, Zhengtao Yu, Philip S. Yu

While in our observation, compared to the rarity of classes, the calibrated uncertainty estimated from well-trained evidential deep learning networks better reflects model performance.

Contrastive Learning Event Detection

Knowledge Graph Context-Enhanced Diversified Recommendation

1 code implementation20 Oct 2023 Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu

Collectively, our contributions signify a substantial stride towards augmenting the panorama of recommendation diversity within the realm of KG-informed RecSys paradigms.

Knowledge Graphs Recommendation Systems

Collaborative Semantic Alignment in Recommendation Systems

no code implementations13 Oct 2023 Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu

However, PLMs often overlook the vital collaborative filtering signals, leading to challenges in merging collaborative and semantic representation spaces and fine-tuning semantic representations for better alignment with warm-start conditions.

Collaborative Filtering Language Modelling +1

Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs

1 code implementation5 Sep 2023 Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He

In this work, we propose a novel unsupervised Skin Lesion sEgmentation framework based on structural entropy and isolation forest outlier Detection, namely SLED.

Lesion Segmentation Outlier Detection +2

Graph-based Alignment and Uniformity for Recommendation

1 code implementation18 Aug 2023 Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

To address this issue, we propose a novel approach, graph-based alignment and uniformity (GraphAU), that explicitly considers high-order connectivities in the user-item bipartite graph.

Collaborative Filtering Recommendation Systems +1

Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System

no code implementations16 Aug 2023 JianGuo Zhang, Stephen Roller, Kun Qian, Zhiwei Liu, Rui Meng, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong

End-to-end task-oriented dialogue (TOD) systems have achieved promising performance by leveraging sophisticated natural language understanding and natural language generation capabilities of pre-trained models.

Natural Language Understanding Retrieval +1

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

no code implementations4 Aug 2023 Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh Murthy, Zeyuan Chen, JianGuo Zhang, Devansh Arpit, ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese

This demonstrates that using policy gradient optimization to improve language agents, for which we believe our work is one of the first, seems promising and can be applied to optimize other models in the agent architecture to enhance agent performances over time.

Language Modelling

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI

1 code implementation19 Jul 2023 JianGuo Zhang, Kun Qian, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Huan Wang, Silvio Savarese, Caiming Xiong

Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversity and comprehensiveness.

Few-Shot Learning Language Modelling +1

Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation

1 code implementation26 Jun 2023 Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu

We explore the role of the fine-grained item attributes in bridging the gaps between the existing and the SCS items and pre-train a knowledgeable item-attribute graph for SCS item recommendation.

Attribute Multi-Task Learning +1

Addressing the Rank Degeneration in Sequential Recommendation via Singular Spectrum Smoothing

no code implementations21 Jun 2023 Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu

We also establish a correlation between the ranks of sequence and item embeddings and the rank of the user-item preference prediction matrix, which can affect recommendation diversity.

Sequential Recommendation

Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training

no code implementations12 May 2023 Ziwei Fan, Zhiwei Liu, Shelby Heinecke, JianGuo Zhang, Huan Wang, Caiming Xiong, Philip S. Yu

This paper presents a novel paradigm for the Zero-Shot Item-based Recommendation (ZSIR) task, which pre-trains a model on product knowledge graph (PKG) to refine the item features from PLMs.

Recommendation Systems

Conditional Denoising Diffusion for Sequential Recommendation

no code implementations22 Apr 2023 Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu

Generative models have attracted significant interest due to their ability to handle uncertainty by learning the inherent data distributions.

Denoising Sequential Recommendation

Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training

no code implementations11 Apr 2023 Juntao Tan, Shelby Heinecke, Zhiwei Liu, Yongjun Chen, Yongfeng Zhang, Huan Wang

Two properties unique to the nature of sequential recommendation models may impair their robustness - the cascade effects induced during training and the model's tendency to rely too heavily on temporal information.

Sequential Recommendation

Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation

1 code implementation28 Jan 2023 Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S Yu

Wasserstein Discrepancy Measurement builds upon the 2-Wasserstein distance, which is more robust, more efficient in small batch sizes, and able to model the uncertainty of stochastic augmentation processes.

Contrastive Learning Mutual Information Estimation +2

MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System

1 code implementation14 Nov 2022 Liangwei Yang, Shen Wang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu

To fill this gap, in this paper, we explore the rich, heterogeneous relationship among items and propose a new KG-enhanced recommendation model called Collaborative Meta-Knowledge Enhanced Recommender System (MetaKRec).

Recommendation Systems

Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph

1 code implementation2 Nov 2022 Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

PA layers efficiently learn the relatedness of non-neighbor nodes to improve the information propagation to users.

Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer

1 code implementation24 Oct 2022 Ziwei Fan, Zhiwei Liu, Chen Wang, Peijie Huang, Hao Peng, Philip S. Yu

However, it remains a significant challenge to model auxiliary item relationships in SR. To simultaneously model high-order item-item transitions in sequences and auxiliary item relationships, we propose a Multi-relational Transformer capable of modeling auxiliary item relationships for SR (MT4SR).

Sequential Recommendation

LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space

1 code implementation26 Sep 2022 Pu Cao, Lu Yang, Dongxu Liu, Zhiwei Liu, Shan Li, Qing Song

In this work, we first point out that these two characteristics are related to the degree of alignment (or disalignment) of the inverse codes with the synthetic distribution.

Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees

1 code implementation4 Sep 2022 Jiaqian Ren, Lei Jiang, Hao Peng, Lingjuan Lyu, Zhiwei Liu, Chaochao Chen, Jia Wu, Xu Bai, Philip S. Yu

Integrating multiple online social networks (OSNs) has important implications for many downstream social mining tasks, such as user preference modelling, recommendation, and link prediction.

Attribute Link Prediction +2

Explanation Guided Contrastive Learning for Sequential Recommendation

1 code implementation3 Sep 2022 Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao

Recently, contrastive learning has been applied to the sequential recommendation task to address data sparsity caused by users with few item interactions and items with few user adoptions.

Contrastive Learning Representation Learning +1

ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation

1 code implementation27 Aug 2022 Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S. Yu

Then we propose Contrastive Variational AutoEncoder (ContrastVAE in short), a two-branched VAE model with contrastive regularization as an embodiment of ContrastELBO for sequential recommendation.

Contrastive Learning Sequential Recommendation

Generating Negative Samples for Sequential Recommendation

no code implementations7 Aug 2022 Yongjun Chen, Jia Li, Zhiwei Liu, Nitish Shirish Keskar, Huan Wang, Julian McAuley, Caiming Xiong

Due to the dynamics of users' interests and model updates during training, considering randomly sampled items from a user's non-interacted item set as negatives can be uninformative.

Sequential Recommendation

Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory

no code implementations24 May 2022 Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu

To incorporate temporal information into the message passing scheme, we introduce a novel temporal-aware aggregator which assigns weights to neighbours according to an adaptive time exponential decay formula.

Event Detection

Improving Contrastive Learning with Model Augmentation

1 code implementation25 Mar 2022 Zhiwei Liu, Yongjun Chen, Jia Li, Man Luo, Philip S. Yu, Caiming Xiong

However, existing methods all construct views by adopting augmentation from data perspectives, while we argue that 1) optimal data augmentation methods are hard to devise, 2) data augmentation methods destroy sequential correlations, and 3) data augmentation fails to incorporate comprehensive self-supervised signals.

Contrastive Learning Data Augmentation +2

Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering

no code implementations SpaNLP (ACL) 2022 Man Luo, Kazuma Hashimoto, Semih Yavuz, Zhiwei Liu, Chitta Baral, Yingbo Zhou

Among several interesting findings, it is important to highlight that (1) the generative readers perform better in long context QA, (2) the extractive readers perform better in short context while also showing better out-of-domain generalization, and (3) the encoder of encoder-decoder PrLMs (e. g., T5) turns out to be a strong extractive reader and outperforms the standard choice of encoder-only PrLMs (e. g., RoBERTa).

Domain Generalization Multi-Task Learning +1

Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network

1 code implementation7 Feb 2022 Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu

We conduct a comprehensive analysis of users' online game behaviors, which motivates the necessity of handling those three characteristics in the online game recommendation.

Recommendation Systems

Intent Contrastive Learning for Sequential Recommendation

1 code implementation5 Feb 2022 Yongjun Chen, Zhiwei Liu, Jia Li, Julian McAuley, Caiming Xiong

Specifically, we introduce a latent variable to represent users' intents and learn the distribution function of the latent variable via clustering.

Contrastive Learning Model Optimization +3

Sequential Recommendation via Stochastic Self-Attention

1 code implementation16 Jan 2022 Ziwei Fan, Zhiwei Liu, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, Philip S. Yu

We further argue that BPR loss has no constraint on positive and sampled negative items, which misleads the optimization.

Sequential Recommendation

Multi-initialization Optimization Network for Accurate 3D Human Pose and Shape Estimation

no code implementations24 Dec 2021 Zhiwei Liu, Xiangyu Zhu, Lu Yang, Xiang Yan, Ming Tang, Zhen Lei, Guibo Zhu, Xuetao Feng, Yan Wang, Jinqiao Wang

In the second stage, we design a mesh refinement transformer (MRT) to respectively refine each coarse reconstruction result via a self-attention mechanism.

Ranked #65 on 3D Human Pose Estimation on 3DPW (MPJPE metric)

3D human pose and shape estimation 3D Reconstruction

Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network

no code implementations28 Nov 2021 Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan

In this paper, we propose a novel Reinforced Attentive Multi-relational Graph Neural Network (RAM-GNN) to the pre-train user and item embeddings on the user and item graph prior to the recommendation step.

Recommendation Systems

Federated Social Recommendation with Graph Neural Network

no code implementations21 Nov 2021 Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu

However, they all require centralized storage of the social links and item interactions of users, which leads to privacy concerns.

Federated Learning Recommendation Systems

Pre-training Graph Neural Network for Cross Domain Recommendation

no code implementations16 Nov 2021 Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu

Then, we transfer the pre-trained graph encoder to initialize the node embeddings on the target domain, which benefits the fine-tuning of the single domain recommender system on the target domain.

Graph Representation Learning Recommendation Systems

Deep Fraud Detection on Non-attributed Graph

no code implementations4 Oct 2021 Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu

The successes of most previous methods heavily rely on rich node features and high-fidelity labels.

Contrastive Learning Fraud Detection

Self-supervised Learning for Sequential Recommendation with Model Augmentation

no code implementations29 Sep 2021 Zhiwei Liu, Yongjun Chen, Jia Li, Man Luo, Philip S. Yu, Caiming Xiong

However, existing methods all construct views by adopting augmentation from data perspectives, while we argue that 1) optimal data augmentation methods are hard to devise, 2) data augmentation methods destroy sequential correlations, and 3) data augmentation fails to incorporate comprehensive self-supervised signals.

Contrastive Learning Data Augmentation +2

DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN

1 code implementation26 Aug 2021 Yu Wang, Zhiwei Liu, Ziwei Fan, Lichao Sun, Philip S. Yu

In the information explosion era, recommender systems (RSs) are widely studied and applied to discover user-preferred information.

Knowledge Graphs Recommendation Systems

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

1 code implementation14 Aug 2021 Ziwei Fan, Zhiwei Liu, Jiawei Zhang, Yun Xiong, Lei Zheng, Philip S. Yu

Therefore, we propose to unify sequential patterns and temporal collaborative signals to improve the quality of recommendation, which is rather challenging.

Sequential Recommendation

Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

1 code implementation14 Aug 2021 Zhiwei Liu, Yongjun Chen, Jia Li, Philip S. Yu, Julian McAuley, Caiming Xiong

In this paper, we investigate the application of contrastive Self-Supervised Learning (SSL) to the sequential recommendation, as a way to alleviate some of these issues.

Contrastive Learning Self-Supervised Learning +1

Quality-Aware Network for Face Parsing

1 code implementation14 Jun 2021 Lu Yang, Qing Song, Xueshi Xin, Wenhe Jia, Zhiwei Liu

This is a very short technical report, which introduces the solution of the Team BUPT-CASIA for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021.

Face Parsing Human Parsing

Relational Graph Neural Network Design via Progressive Neural Architecture Search

no code implementations30 May 2021 Ailing Zeng, Minhao Liu, Zhiwei Liu, Ruiyuan Gao, Jing Qin, Qiang Xu

We propose a novel solution to addressing a long-standing dilemma in the representation learning of graph neural networks (GNNs): how to effectively capture and represent useful information embedded in long-distance nodes to improve the performance of nodes with low homophily without leading to performance degradation in nodes with high homophily.

Neural Architecture Search Node Classification +1

Quality-Aware Network for Human Parsing

1 code implementation10 Mar 2021 Lu Yang, Qing Song, Zhihui Wang, Zhiwei Liu, Songcen Xu, Zhihao LI

How to estimate the quality of the network output is an important issue, and currently there is no effective solution in the field of human parsing.

Human Parsing Instance Segmentation +1

Deoscillated Graph Collaborative Filtering

1 code implementation4 Nov 2020 Zhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang, Philip S. Yu

Stacking multiple cross-hop propagation layers and locality layers constitutes the DGCF model, which models high-order CF signals adaptively to the locality of nodes and layers.

Collaborative Filtering Recommendation Systems

Basket Recommendation with Multi-Intent Translation Graph Neural Network

1 code implementation22 Oct 2020 Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu

The problem of basket recommendation~(BR) is to recommend a ranking list of items to the current basket.

Relation Translation

Identity-Guided Human Semantic Parsing for Person Re-Identification

1 code implementation ECCV 2020 Kuan Zhu, Haiyun Guo, Zhiwei Liu, Ming Tang, Jinqiao Wang

In this paper, we propose the identity-guided human semantic parsing approach (ISP) to locate both the human body parts and personal belongings at pixel-level for aligned person re-ID only with person identity labels.

Clustering Human Parsing +3

CodeMatcher: Searching Code Based on Sequential Semantics of Important Query Words

no code implementations29 May 2020 Chao Liu, Xin Xia, David Lo, Zhiwei Liu, Ahmed E. Hassan, Shanping Li

CodeMatcher first collects metadata for query words to identify irrelevant/noisy ones, then iteratively performs fuzzy search with important query words on the codebase that is indexed by the Elasticsearch tool, and finally reranks a set of returned candidate code according to how the tokens in the candidate code snippet sequentially matched the important words in a query.

Code Search Information Retrieval +1

Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection

1 code implementation1 May 2020 Zhiwei Liu, Yingtong Dou, Philip S. Yu, Yutong Deng, Hao Peng

In this paper, we introduce these inconsistencies and design a new GNN framework, $\mathsf{GraphConsis}$, to tackle the inconsistency problem: (1) for the context inconsistency, we propose to combine the context embeddings with node features, (2) for the feature inconsistency, we design a consistency score to filter the inconsistent neighbors and generate corresponding sampling probability, and (3) for the relation inconsistency, we learn a relation attention weights associated with the sampled nodes.

Fraud Detection Relation

BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network

1 code implementation14 Jan 2020 Zhiwei Liu, Mengting Wan, Stephen Guo, Kannan Achan, Philip S. Yu

By defining a basket entity to represent the basket intent, we can model this problem as a basket-item link prediction task in the User-Basket-Item~(UBI) graph.

Collaborative Filtering Link Prediction

A Large-Scale Deep Architecture for Personalized Grocery Basket Recommendations

no code implementations24 Oct 2019 Aditya Mantha, Yokila Arora, Shubham Gupta, Praveenkumar Kanumala, Zhiwei Liu, Stephen Guo, Kannan Achan

In this paper, we introduce a production within-basket grocery recommendation system, RTT2Vec, which generates real-time personalized product recommendations to supplement the user's current grocery basket.

JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation

1 code implementation18 Oct 2019 Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu

JSCN will simultaneously operate multi-layer spectral convolutions on different graphs, and jointly learn a domain-invariant user representation with a domain adaptive user mapping module.

Recommendation Systems

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