activity
20222024
most citedDisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation

5 citations · 15 across the 7 of their papers we have counts for

collaborators

6 papers

cs.IR2024

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias

Miaomiao Cai, Lei Chen, Yifan Wang +5

Collaborative Filtering (CF) typically suffers from the significant challenge of popularity bias due to the uneven distribution of items in real-world datasets. This bias leads to…

math.NA20242 cited

Tensor Neural Network Interpolation and Its Applications

Yongxin Li, Zhongshuo Lin, Yifan Wang +1

Based on tensor neural network, we propose an interpolation method for high dimensional non-tensor-product-type functions. This interpolation scheme is designed by using the tensor…

cs.CL2023

Eliminating Reasoning via Inferring with Planning: A New Framework to Guide LLMs' Non-linear Thinking

Yongqi Tong, Yifan Wang, Dawei Li +4

Chain-of-Thought(CoT) prompting and its variants explore equipping large language models (LLMs) with high-level reasoning abilities by emulating human-like linear cognition and log…

cs.LG20233 cited

TGNN: A Joint Semi-supervised Framework for Graph-level Classification

Wei Ju, Xiao Luo, Meng Qu +5

This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adop…

cs.CL20233 cited

Automatic Generation of German Drama Texts Using Fine Tuned GPT-2 Models

Mariam Bangura, Kristina Barabashova, Anna Karnysheva +2

This study is devoted to the automatic generation of German drama texts. We suggest an approach consisting of two key steps: fine-tuning a GPT-2 model (the outline model) to genera…

cs.LG20222 cited

A Knowledge Distillation-Based Backdoor Attack in Federated Learning

Yifan Wang, Wei Fan, Keke Yang +2

Federated Learning (FL) is a novel framework of decentralized machine learning. Due to the decentralized feature of FL, it is vulnerable to adversarial attacks in the training proc…