1 citations · 2 across the 5 of their papers we have counts for
6 papers
ForTress: Bringing Assurance and Determinism for LLM-Driven Fortran-to-Python Translation
Qinrun Dai, Ruitong Liu, Chien-Wei Huang +3
Modernizing mature scientific software from Fortran to Python can improve accessibility and integration with modern computing tools, but manual rewriting is expensive. Large langua…
Understanding Gaps in LLM Pipelines Towards Scalable Fuzzing Harness Generation: An Empirical Study and Enhancement
Kang Yang, Yunhang Zhang, Zichuan Li +3
Large language model (LLM)-based techniques have achieved notable progress in fuzz harness generation. However, applying them to arbitrary functions \textit{at scale} remains diffi…
Blackbox Dataset Inference for LLM
Ruikai Zhou, Kang Yang, Xun Chen +3
Today, the training of large language models (LLMs) can involve personally identifiable information and copyrighted material, incurring dataset misuse. To mitigate the problem of d…
Alleviating the Fear of Losing Alignment in LLM Fine-tuning
Kang Yang, Guanhong Tao, Xun Chen +1
Large language models (LLMs) have demonstrated revolutionary capabilities in understanding complex contexts and performing a wide range of tasks. However, LLMs can also answer ques…
Rethinking the Evaluation of Secure Code Generation
Shih-Chieh Dai, Jun Xu, Guanhong Tao
Large language models (LLMs) are widely used in software development. However, the code generated by LLMs often contains vulnerabilities. Several secure code generation methods hav…
Exploiting Watermark-Based Defense Mechanisms in Text-to-Image Diffusion Models for Unauthorized Data Usage
Soumil Datta, Shih-Chieh Dai, Leo Yu +1
Text-to-image diffusion models, such as Stable Diffusion, have shown exceptional potential in generating high-quality images. However, recent studies highlight concerns over the us…