Junhong Lin

According to our database, Junhong Lin authored at least 12 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

ConstellationNet: Reinventing Clustering Through GNNs.

Aidan Gao, Junhong Lin

Mach. Learn., April, 2026

How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge.

Junhong Lin, Bing Zhang, Song Wang, Ziyan Liu, Dan Gutfreund, Julian Shun, Yada Zhu

CoRR, February, 2026

HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs.

Xinyue Zeng, Junhong Lin, Yujun Yan, Feng Guo, Liang Shi, Jun Wu, Dawei Zhou

CoRR, January, 2026

2025

Temporal Reasoning with Large Language Models Augmented by Evolving Knowledge Graphs.

Junhong Lin, Song Wang, Xiaojie Guo, Julian Shun, Yada Zhu

CoRR, September, 2025

Plan and Budget: Effective and Efficient Test-Time Scaling on Large Language Model Reasoning.

Junhong Lin, Xinyue Zeng, Jie Zhu, Song Wang, Julian Shun, Jun Wu, Dawei Zhou

CoRR, May, 2025

ConstellationNet: Reinventing Spatial Clustering through GNNs.

Aidan Gao, Junhong Lin

CoRR, March, 2025

When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark.

Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Yada Zhu, Julian Shun

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection.

Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, Dawei Zhou

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Reasoning of Large Language Models over Knowledge Graphs with Super-Relations.

Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods.

Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun

CoRR, 2024

FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection.

Junhong Lin, Xiaojie Guo, Yada Zhu, Samuel Mitchell, Erik Altman, Julian Shun

Proceedings of the 5th ACM International Conference on AI in Finance, 2024

UnifiedGT: Towards a Universal Framework of Transformers in Large-Scale Graph Learning.

Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun

Proceedings of the IEEE International Conference on Big Data, 2024