3 papers
cs.SE2026
TRACER: A Semantic-Aware Framework for Fine-Grained Contamination Detection in Code LLMs
Yifeng Di, Xuliang Huang, Tianyi Zhang
Data contamination is a known threat to the reliability of model evaluation. However, it remains underexplored in code large language models (LLMs), where contamination often goes…
cs.CL2024
Quantifying Generalization Complexity for Large Language Models
Zhenting Qi, Hongyin Luo, Xuliang Huang +5
While large language models (LLMs) have shown exceptional capabilities in understanding complex queries and performing sophisticated tasks, their generalization abilities are often…
cs.LG2024
Harmonizing Human Insights and AI Precision: Hand in Hand for Advancing Knowledge Graph Task
Shurong Wang, Yufei Zhang, Xuliang Huang +1
Knowledge graph embedding (KGE) has caught significant interest for its effectiveness in knowledge graph completion (KGC), specifically link prediction (LP), with recent KGE models…