8 accepted papers
This paper focuses on a key challenge in Neural Architecture Search (NAS): integrating established architectural knowledge while exploring new designs under expensive evaluations. Large language models (LLMs) are a promising assistant for NAS because they can translate rich architectural and coding …
Vision-Language-Action (VLA) models typically bridge the gap between perceptual and action spaces by pre-training a large-scale Vision-Language Model (VLM) on robotic data. While this approach greatly enhances performance, it also incurs significant training costs. In this paper, we investigate how
Adversarial attacks are essential for evaluating the robustness of deep learning-based forensics, revealing potential vulnerabilities. However, most existing adversarial sample generation methods face significant trade-offs between anti-forensic ability, transferability, and visual quality, as they…
Accurately recommending candidate news articles to users has always been the core challenge of news recommendation system. News recommendations often require modeling of user interest to match candidate news. Recent efforts have primarily focused on extracting local subgraph information in a global…
Advanced persistent threats (APTs) pose significant risks to national infrastructure and corporate security. System logs record interactions between system entities, which are widely used for APT detection. However, the complex syntax and intricate relationships in system logs pose significant chall…
Text style transfer (TST) aims to flexibly adjust the style of text while preserving its core content. Although large language models (LLMs) excel in TST tasks, they often face unidirectional issues due to imbalanced training data and their tendency to generate safer responses. These challenges pres…
Path planning in uneven terrain scenarios is one of the core capabilities of intelligent off-road robots and vehicles. The complex terrain undulations often cause bumpy motion and sharp turns along the planned path, making smooth and safe path planning challenging. Most path planning methods in this
In recent years, linguistic generative steganography has been greatly developed. Current linguistic steganography methods can generate sufficiently fluent steganographic text, but cannot control the semantic expression of the generated steganographic text. In social network, steganographic text with…