115 citations · 263 across the 14 of their papers we have counts for
Showing 2023Show all
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cs.LG2023★ 3 cited
Good-looking but Lacking Faithfulness: Understanding Local Explanation Methods through Trend-based Testing
Jinwen He, Kai Chen, Guozhu Meng +2
While enjoying the great achievements brought by deep learning (DL), people are also worried about the decision made by DL models, since the high degree of non-linearity of DL mode…
cs.CR2023★ 28 cited
Demystifying RCE Vulnerabilities in LLM-Integrated Apps
Tong Liu, Zizhuang Deng, Guozhu Meng +2
LLMs show promise in transforming software development, with a growing interest in integrating them into more intelligent apps. Frameworks like LangChain aid LLM-integrated app dev…
cs.SE2023★ 2 cited
ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning
Shangqing Liu, Bozhi Wu, Xiaofei Xie +2
Large-scale pre-trained models such as CodeBERT, GraphCodeBERT have earned widespread attention from both academia and industry. Attributed to the superior ability in code represen…