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Sun and the CERT recommend for secure Java development to not allow partially initialized objects to be accessed. The CERT considers the severity of the risks taken by not following this recommendation as high. The solution currently used…
Anonymization of voice seeks to conceal the identity of the speaker while maintaining the utility of speech data. However, residual speaker cues often persist, which pose privacy risks. We propose SegReConcat, a data augmentation method for…
Execution of quantum algorithms on large-scale quantum computers will require extremely low logical error rates, which necessitates the development of scalable decoding architectures. Local decoders are promising candidates for this task,…
Label noise and long-tailed distributions are two major challenges in distantly supervised relation extraction. Recent studies have shown great progress on denoising, but paid little attention to the problem of long-tailed relations. In…
Recently, cybersecurity becomes more and more important due to the rapid development of Internet. However, existing methods are in reality highly sensitive to attacks and are far more vulnerable than expected, as they are lack of trustable…
We introduce Object Graph Programming (OGO), which enables reading and modifying an object graph (i.e., the entire state of the object heap) via declarative queries. OGO models the objects and their relations in the heap as an object graph…
Discrete audio tokens are compact representations that aim to preserve perceptual quality, phonetic content, and speaker characteristics while enabling efficient storage and inference, as well as competitive performance across diverse…
High-performance deep learning depends on efficient tensor programs. In recent years, automatic tensor program optimization, also known as tensor compilation, has emerged as the primary approach to generating efficient tensor programs.…
Malware analysis systems, including dynamic-analysis sandboxes and digital forensics and incident response (DFIR) platforms, rely on telemetry pipelines comprising collection agents, serializers, and database backends to capture and present…
Scene graphs (SGs) represent objects and their relationships as structured graphs, enabling applications in image generation, robotics, and 3D understanding. Recent work suggests that conditioning image generation on scene graphs improves…
We introduce a scalable, modular, and sound approach for automatically constructing formal security specifications for Java bytecode programs in the form of method summaries. A summary provides an abstract representation of a method's…
In the past decade, object detection tasks are defined mostly by large public datasets. However, building object detection datasets is not scalable due to inefficient image collecting and labeling. Furthermore, most labels are still in the…
Accurately controlling object count in text-to-image generation remains a key challenge. Supervised methods often fail, as training data rarely covers all count variations. Methods that manipulate the denoising process to add or remove…
Recently, Graph Neural Network (GNN)-based vulnerability detection systems have achieved remarkable success. However, the lack of explainability poses a critical challenge to deploy black-box models in security-related domains. For this…
Session-based recommendation is a practical recommendation task that predicts the next item based on an anonymous behavior sequence, and its performance relies heavily on the transition information between items in the sequence. The SOTA…
The paper explores a novel methodology in source code obfuscation through the application of text-based recurrent neural network (RNN) encoder-decoder models in ciphertext generation and key generation. Sequence-to-sequence models are…
When it comes to addressing the safety/security related needs at different production/construction sites, accurate detection of the presence of workers, vehicles, equipment important and formed an integral part of computer vision-based…
Knowing what sensitive resources a dependency could potentially access would help developers assess the risk of a dependency before selection. One way to get an understanding of the potential sensitive resource usage by a dependency is…
Mobile applications (apps) often transmit sensitive data through network with various intentions. Some transmissions are needed to fulfill the app's functionalities. However, transmissions with malicious receivers may lead to privacy…
This article introduces a novel method for object-level relocalization of robotic systems. It determines the pose of a camera sensor by robustly associating the object detections in the current frame with 3D objects in a lightweight…