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20232026
most citedAn Empirical Study on JIT Defect Prediction Based on BERT-style Model

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Greedy-Gnorm: A Gradient Matrix Norm-Based Alternative to Attention Entropy for Head Pruning

Yuxi Guo, Paul Sheridan

Attention head pruning has emerged as an effective technique for transformer model compression, an increasingly important goal in the era of Green AI. However, existing pruning met…

cs.CL2025

A RoBERTa-Based Functional Syntax Annotation Model for Chinese Texts

Han Xiaohui, Zhang Yunlong, Guo Yuxi

Systemic Functional Grammar and its branch, Cardiff Grammar, have been widely applied to discourse analysis, semantic function research, and other tasks across various languages an…

cs.CL2024

TODO: Enhancing LLM Alignment with Ternary Preferences

Yuxiang Guo, Lu Yin, Bo Jiang +1

Aligning large language models (LLMs) with human intent is critical for enhancing their performance across a variety of tasks. Standard alignment techniques, such as Direct Prefere…

cs.SE2024★ 2 cited

An Empirical Study on JIT Defect Prediction Based on BERT-style Model

Yuxiang Guo, Xiaopeng Gao, Bo Jiang

Previous works on Just-In-Time (JIT) defect prediction tasks have primarily applied pre-trained models directly, neglecting the configurations of their fine-tuning process. In this…

cs.CL2023

SCCA: Shifted Cross Chunk Attention for long contextual semantic expansion

Yuxiang Guo

Sparse attention as a efficient method can significantly decrease the computation cost, but current sparse attention tend to rely on window self attention which block the global in…

cs.SE2023

A study on the impact of pre-trained model on Just-In-Time defect prediction

Yuxiang Guo, Xiaopeng Gao, Zhenyu Zhang +2

Previous researchers conducting Just-In-Time (JIT) defect prediction tasks have primarily focused on the performance of individual pre-trained models, without exploring the relatio…