AI RESEARCH
LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification
arXiv CS.LG
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ArXi:2603.03959v3 Announce Type: replace-cross Code comment classification is a critical task for automated software documentation and analysis. In the context of the NLBSE'26 Tool Competition, we present LoRA-MME, a Multi-Model Ensemble architecture utilizing Parameter-Efficient Fine-Tuning (PEFT). Our approach addresses the multi-label classification challenge across Java, Python, and Pharo by combining the strengths of four distinct transformer encoders: UniXcoder, CodeBERT, GraphCodeBERT, and CodeBERTa.