Papers by Bolin Chen

3 papers
Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection (2022.coling-1)

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Challenge: Existing methods to detect fake news focus on mining lexical and syntactic features.
Approach: They propose a topology imbalance and Relation inauthenticity aware Hierarchical Graph Attention Networks to identify fake news on social media.
Outcome: The proposed method outperforms state-of-the-art methods on real-world datasets.
Editing the Moving World: Model Editing for Video LLMs (2026.acl-long)

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Challenge: Existing models for knowledge editing focus on knowledge-level or static visual domains, overlooking dynamic semantics.
Approach: They propose a benchmark for modeling large language models using six representative models . they analyze the strengths and limitations of existing models and identify new directions .
Outcome: The proposed benchmark extends existing models from static modalities to dynamic video scenarios.
LLM-Based Multi-Agent Systems are Scalable Graph Generative Models (2025.findings-acl)

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Challenge: Social graphs are mathematical structures stem from pairwise interactions between entities through nodes and edges.
Approach: They propose a framework for dynamic, text-attributed social graph generation that simulates the temporal node and edge generation processes for zero-shot social graphs.
Outcome: The proposed framework improves macroscopic graph structure metrics by 11% . the proposed model can generate graphs with up to 100,000 nodes or 10 million edges .

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