activity
20152023
most citedKnowledge Graph Contrastive Learning for Recommendation

483 citations · 1.3k across the 23 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

math.NA2023

A New Extrapolation Economy Cascadic Multigrid Method for Image Restoration Problems

Zhaoteng Chu, Ziqi Yan, Chenliang Li

In this paper, a new extrapolation economy cascadic multigrid method is proposed to solve the image restoration model. The new method combines the new extrapolation formula and qua…

cs.IR2023★ 4 cited

Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community

Qingyao Ai, Ting Bai, Zhao Cao +30

The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Mod…

cs.IR2023★ 16 cited

Multi-Scenario Ranking with Adaptive Feature Learning

Yu Tian, Bofang Li, Si Chen +6

Recently, Multi-Scenario Learning (MSL) is widely used in recommendation and retrieval systems in the industry because it facilitates transfer learning from different scenarios, mi…

math.NA2023

A Class of Smoothing Modulus-Based Iterative Method for Solving Implicit Complementarity Problems

Cong Guo, Chenliang Li, Tao Luo

In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit compleme…

cs.CL2023★ 85 cited

On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training

Hao Fei, Tat-Seng Chua, Chenliang Li +3

Aspect-based sentiment analysis (ABSA) aims at automatically inferring the specific sentiment polarities toward certain aspects of products or services behind the social media text…

cs.IR2023★ 22 cited

DiffuRec: A Diffusion Model for Sequential Recommendation

Zihao Li, Aixin Sun, Chenliang Li

Mainstream solutions to Sequential Recommendation (SR) represent items with fixed vectors. These vectors have limited capability in capturing items' latent aspects and users' diver…