RevGNN: Negative Sampling Enhanced Contrastive Graph Learning for Academic Reviewer Recommendation
Acquiring reviewers for academic submissions is a challenging recommendation scenario.
Recent graph learning-driven models have made remarkable progress in the field of …
Recent graph learning-driven models have made remarkable progress in the field of …
MCAP: Low-Pass GNNs with Matrix Completion for Academic Recommendations
Graph Neural Networks (GNNs) are commonly used and have shown promising
performance in recommendation systems. A major branch, Heterogeneous GNNs, models …
performance in recommendation systems. A major branch, Heterogeneous GNNs, models …
LLMs can realize combinatorial creativity: generating creative ideas via LLMs for scientific research
T Gu, J Wang, Z Zhang, HH Li - arXiv preprint arXiv:2412.14141, 2024 - arxiv.org
Scientific idea generation has been extensively studied in creativity theory and
computational creativity research, providing valuable frameworks for understanding and …
computational creativity research, providing valuable frameworks for understanding and …
Multi-Scale Heterogeneous Text-Attributed Graph Datasets From Diverse Domains
Heterogeneous Text-Attributed Graphs (HTAGs), where different types of entities are not
only associated with texts but also connected by diverse relationships, have gained …
only associated with texts but also connected by diverse relationships, have gained …
MIND: Effective Incorrect Assignment Detection through a Multi-Modal Structure-Enhanced Language Model
The rapid growth of academic publications has exacerbated the issue of author name
ambiguity in online digital libraries. Despite advances in name disambiguation algorithms …
ambiguity in online digital libraries. Despite advances in name disambiguation algorithms …
The Solution for The PST-KDD-2024 OAG-Challenge
S Zhong, X Li, S Jin, Y Yang - arXiv preprint arXiv:2407.12827, 2024 - arxiv.org
In this paper, we introduce the second-place solution in the KDD-2024 OAG-Challenge
paper source tracing track. Our solution is mainly based on two methods, BERT and GCN …
paper source tracing track. Our solution is mainly based on two methods, BERT and GCN …
Text-Driven Neural Collaborative Filtering Model for Paper Source Tracing
A Xu, B Chang, Q Liu, L Jian - arXiv preprint arXiv:2407.17722, 2024 - arxiv.org
Identifying significant references within the complex interrelations of a citation knowledge
graph is challenging, which encompasses connections through citations, authorship …
graph is challenging, which encompasses connections through citations, authorship …
LLM-Powered Ensemble Learning for Paper Source Tracing: A GPU-Free Approach
We participated in the KDD CUP 2024 paper source tracing competition and achieved the
3rd place. This competition tasked participants with identifying the reference sources (ie, ref …
3rd place. This competition tasked participants with identifying the reference sources (ie, ref …
An Ensemble Model with Multi-Scale Features for Incorrect Assignment Detection
M Shen - KDD 2024 OAG-Challenge Cup, 2024 - openreview.net
With the number of the publication increasing, the name ambiguity problem is becoming
increasingly complex. To improve this research, OGA-Challenge Team published a large …
increasingly complex. To improve this research, OGA-Challenge Team published a large …
Advancing Academic Knowledge Retrieval via LLM-enhanced Representation Similarity Fusion
W Dai, P Fu, C Gan - arXiv preprint arXiv:2410.10455, 2024 - arxiv.org
In an era marked by robust technological growth and swift information renewal, furnishing
researchers and the populace with top-tier, avant-garde academic insights spanning various …
researchers and the populace with top-tier, avant-garde academic insights spanning various …