arXiv:2601.19747v2 Announce Type: replace-cross
Abstract: In the rapidly evolving field of Electronic Design Automation (EDA), the deployment of Large Language Models (LLMs) for Register-Transfer Lev...
By Jiale Liu, Taiyu Zhou, Tianqi Jiang
The paper introduces MAGS, a multi-agent framework that automatically generates executable programs with formal safety guarantees. MAGS translates LLM-generated code into the verification-aware language Dafny, repairs any safety violations using verifier feedback, and then compiles the verified code back into executable form. Evaluations on 220 diverse examples—including CUDA kernels, terminal scripts, and robotic-arm tasks—show a 100% success rate in producing programs that meet frozen safety specifications, with additional safety and functional tests confirming strong performance across domains.
By Albert Wu, Nicholas Roberts, Tzu-Heng Huang, Haoran Lin, Gil Friedman, Sungjun Cho, Gabriel Orlanski, Frederic Sala
arXiv:2606. 14327v1 Announce Type: cross Abstract: This paper appraises recent frameworks within AI development to integrate LLMs into control tasks in automotive contexts from the perspective of safety assurance.
By Shaun Feakins, Ibrahim Habli, Kim Littler, Robert Palin
The paper surveys how large language models (LLMs) are being used in hardware verification, covering tasks such as assertion generation, testbench creation, bug localization, and formal reasoning. It categorizes the literature by methodology, verification goal, tool interaction, benchmarks, and evaluation metrics, and distinguishes between inference-time techniques (prompting, retrieval, structured reasoning, agentic workflows) and training-time adaptation. The authors highlight that LLMs excel as semantic reasoning, search, and orchestration components within verification workflows, yet emphasize the need for semantic alignment, scalable integration, generalization, and rigorous evaluation to ensure true verification correctness.
By Hao Zheng, Jaime Rafael Imperial, Bardia Nadimi, Xiangfei Kong
arXiv:2608. 14590v1 Announce Type: new Abstract: LLM agents increasingly perform irreversible real-world actions, including database updates, API calls, file operations, and autonomous use of tools.
By Pierre Dantas, Lucas Cordeiro, Ehsan Nowroozi, Tihanyi Norbert
arXiv:2608. 13450v1 Announce Type: cross Abstract: Autonomous vehicles depend on large safety-critical software stacks, where weaknesses reachable from adversarial inputs may affect steering, braking, or other control decisions.
By Md Wasiul Haque, Sagar Dasgupta, Mizanur Rahman, Md Rayhanur Rahman