7 citations · 8 across the 7 of their papers we have counts for
7 papers
Code-MUE: Measuring Code LLMs' Uncertainty through Execution-based Semantic Interaction Graphs
Xiaoning Ren, Yinxing Xue, Lei Ma +1
As Code Large Language Models (LLMs) become central to modern software engineering, their inherent stochasticity poses significant real-world risks, where even minor errors can lea…
ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models
Zhuowen Yin, Chongyang Liu, Wenzhang Yang +2
Embodied Foundation Models (EFMs) integrate multimodal understanding, future-state reasoning, and executable robot actions. Yet their safety alignment for human-injury prevention r…
Demystifying the Evolution of Neural Networks with BOM Analysis: Insights from a Large-Scale Study of 55,997 GitHub Repositories
Xiaoning Ren, Yuhang Ye, Xiongfei Wu +2
Neural networks have become integral to many fields due to their exceptional performance. The open-source community has witnessed a rapid influx of neural network (NN) repositories…
Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning
Xiaoning Ren, Qiang Hu, Wei Ma +6
Large language models (LLMs) have recently shown impressive results on diverse code-related tasks, benefiting from large-scale training and instruction tuning. However, studies rev…
Self and Cross-Model Distillation for LLMs: Effective Methods for Refusal Pattern Alignment
Jie Li, Yi Liu, Chongyang Liu +4
Large Language Models (LLMs) like OpenAI's GPT series, Anthropic's Claude, and Meta's LLaMa have shown remarkable capabilities in text generation. However, their susceptibility to…
TGMM: Combining Parse Tree with GPU for Scalable Multilingual and Multi-Granularity Code Clone Detection
Yuhang Ye, Yuekun Wang, Yinxing Xue +2
The rapid evolution of programming languages and software systems has necessitated the implementation of multilingual and scalable clone detection tools. However, it is difficult t…
A Cross-Language Investigation into Jailbreak Attacks in Large Language Models
Jie Li, Yi Liu, Chongyang Liu +5
Large Language Models (LLMs) have become increasingly popular for their advanced text generation capabilities across various domains. However, like any software, they face security…