arXiv:2606. 27960v1 Announce Type: cross Abstract: Software engineering is an intellectually demanding, creative discipline that juggles a web of interdependent tasks to design, build, and assure the quality of increasingly complex systems.
arXiv:2608. 02638v1 Announce Type: cross Abstract: Artificial Intelligence (AI) components are increasingly pervasive in several software systems, including Cyber-Physical Systems (CPSs).
arXiv:2608. 04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention.
arXiv:2602. 07666v4 Announce Type: replace-cross Abstract: DARPA's AI Cyber Challenge (AIxCC, 2023--2025) is the largest competition to date for building fully autonomous cyber reasoning systems (CRSs) that leverage recent advances in AI -- particularly large language models (LLMs) -- to discover and remediate vulnerabilities in real-world open-source software.
arXiv:2604. 10311v2 Announce Type: replace Abstract: Artificial Intelligence (AI) models, encompassing both traditional machine learning (ML) and more advanced approaches such as deep learning and large language models (LLMs), play a central role in modern applications.
arXiv:2606. 05770v1 Announce Type: cross Abstract: AI is changing how software engineers work, but it often comes with hidden burdens and costs.
arXiv:2608. 16237v1 Announce Type: cross Abstract: Building operations are energy-inefficient.
arXiv:2607. 16845v1 Announce Type: new Abstract: Scientists at European XFEL conduct experiments that generate very large and complex datasets.
arXiv:2411. 18714v3 Announce Type: replace-cross Abstract: Self-driving cars increasingly rely on deep neural networks to achieve human-like driving.
arXiv:2607. 10878v1 Announce Type: new Abstract: AI agents are evolving from answer engines into persistent teams that use tools, delegate work, learn from experience, and modify the artifacts that shape their future behavior.
arXiv:2606. 18874v1 Announce Type: new Abstract: AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claims often remains implicit inside model inference.
arXiv:2608. 14407v1 Announce Type: new Abstract: We present a survey of the past and future of AI Scientists: machines capable of automating science.
arXiv:2605. 23809v2 Announce Type: replace-cross Abstract: The Open Radio Access Network (O-RAN) architecture allows AI to be embedded directly into the RAN through modular xApps and rApps, yet creating these applications collecting data, training models, writing code, and deploying them safely remains slow and largely manual.