activity
20172026
most citedDeep Graph Contrastive Representation Learning

413 citations · 1k across the 69 of their papers we have counts for

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Showing cs.IRShow all

27 papers · 1 filter

cs.IR2025

Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation

Liuji Chen, Xiaofang Yang, Yuanzhuo Lu +6

Retrieval-Augmented Generation (RAG) systems improve the factual grounding of large language models (LLMs) but remain vulnerable to retrieval poisoning, where adversaries seed the…

cs.IR20241 cited

Modality-Balanced Learning for Multimedia Recommendation

Jinghao Zhang, Guofan Liu, Qiang Liu +2

Many recommender models have been proposed to investigate how to incorporate multimodal content information into traditional collaborative filtering framework effectively. The use…

cs.IR20246 cited

Can Large Language Models Detect Rumors on Social Media?

Qiang Liu, Xiang Tao, Junfei Wu +2

In this work, we investigate to use Large Language Models (LLMs) for rumor detection on social media. However, it is challenging for LLMs to reason over the entire propagation info…

cs.IR2023

Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation

Jinghao Zhang, Qiang Liu, Shu Wu +1

Multimedia content is of predominance in the modern Web era. In real scenarios, multiple modalities reveal different aspects of item attributes and usually possess different import…

cs.IR20232 cited

Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation

Qiang Liu, Zhaocheng Liu, Zhenxi Zhu +2

Recently, multi-interest models, which extract interests of a user as multiple representation vectors, have shown promising performances for sequential recommendation. However, non…

cs.IR202121 cited

Relation-aware Heterogeneous Graph for User Profiling

Qilong Yan, Yufeng Zhang, Qiang Liu +2

User profiling has long been an important problem that investigates user interests in many real applications. Some recent works regard users and their interacted objects as entitie…