Search Results for author:
Found 4 papers, 1 papers with code
Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
In addition, our user study shows that the vulnerability knowledge generated by Vul-RAG can serve as high-quality explanations which can improve the manual detection accuracy from 0. 60 to 0. 77.
ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation
Third, we find that generating the entire class all at once (i. e. holistic generation strategy) is the best generation strategy only for GPT-4 and GPT-3. 5, while method-by-method generation (i. e. incremental and compositional) is better strategies for the other models with limited ability of understanding long instructions and utilizing the middle information.
On the Relations of Correlation Filter Based Trackers and Struck
In recent years, two types of trackers, namely correlation filter based tracker (CF tracker) and structured output tracker (Struck), have exhibited the state-of-the-art performance.
Multi-Kernel Correlation Filter for Visual Tracking
In this paper, we will derive a multi-kernel correlation filter (MKCF) based tracker which fully takes advantage of the invariance-discriminative power spectrums of various features to further improve the performance.
