5 papers
Fairness Is Not Just Ethical: Performance Trade-Off via Data Correlation Tuning to Mitigate Bias in ML Software
Ying Xiao, Shangwen Wang, Sicen Liu +4
Traditional software fairness research typically emphasizes ethical and social imperatives, neglecting that fairness fundamentally represents a core software quality issue arising…
EMSEdit: Efficient Multi-Step Meta-Learning-based Model Editing
Xiaopeng Li, Shasha Li, Xi Wang +7
Large Language Models (LLMs) power numerous AI applications, yet updating their knowledge remains costly. Model editing provides a lightweight alternative through targeted paramete…
Rethinking Residual Distribution in Locate-then-Edit Model Editing
Xiaopeng Li, Shanwen Wang, Shasha Li +4
Model editing enables targeted updates to the knowledge of large language models (LLMs) with minimal retraining. Among existing approaches, locate-then-edit methods constitute a pr…
Model Editing for LLMs4Code: How Far are We?
Xiaopeng Li, Shangwen Wang, Shasha Li +6
Large Language Models for Code (LLMs4Code) have been found to exhibit outstanding performance in the software engineering domain, especially the remarkable performance in coding ta…
LSAQ: Layer-Specific Adaptive Quantization for Large Language Model Deployment
Binrui Zeng, Bin Ji, Xiaodong Liu +7
As Large Language Models (LLMs) demonstrate exceptional performance across various domains, deploying LLMs on edge devices has emerged as a new trend. Quantization techniques, whic…