Search Results
LLM-SAP: Large Language Models Situational Awareness Based Planning
This study explores integrating large language models (LLMs) with situational awareness-based planning (SAP) to enhance the decision-making capabilities of AI agents in dynamic and uncertain environments.
SAP Signavio Academic Models: A Large Process Model Dataset
In this paper, we introduce the SAP Signavio Academic Models (SAP-SAM) dataset, a collection of hundreds of thousands of business models, mainly process models in BPMN notation.
Other Computer Science Software Engineering
Impact assessment for vulnerabilities in open-source software libraries
Software applications integrate more and more open-source software (OSS) to benefit from code reuse.
Cryptography and Security Software Engineering
Beyond Metadata: Code-centric and Usage-based Analysis of Known Vulnerabilities in Open-source Software
The use of open-source software (OSS) is ever-increasing, and so is the number of open-source vulnerabilities being discovered and publicly disclosed.
Cryptography and Security Software Engineering
Deep Learning with Differential Privacy
Machine learning techniques based on neural networks are achieving remarkable results in a wide variety of domains.
Differentially Private Federated Learning: A Client Level Perspective
In such an attack, a client's contribution during training and information about their data set is revealed through analyzing the distributed model.
SeqTrans: Automatic Vulnerability Fix via Sequence to Sequence Learning
Results show that the accuracy of SeqTrans outperforms the latest techniques and achieves 23. 3% in statement-level fix and 25. 3% in CVE-level fix.
Cryptography and Security Software Engineering
SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness
SAP applied to the CIFAR dataset with 25% synthetic corruption show upto 6% generalization improvements.
A Survey on Machine Learning Techniques for Source Code Analysis
This paper aims to summarize the current knowledge in applied machine learning for source code analysis.
SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency
To bridge the gap between the reference points of salient queries and Transformer detectors, we propose SAlient Point-based DETR (SAP-DETR) by treating object detection as a transformation from salient points to instance objects.
