arXiv:2506.05606v5 Announce Type: replace
Abstract: Can large language models (LLMs) accurately simulate the next web action of a specific user? While LLMs have shown promising capabilities in generating “believable” human behaviors, evaluating thei…
arXiv:2604.16586v1 Announce Type: new
Abstract: Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and biological behavior. This survey traces four complem…
arXiv:2604.16341v1 Announce Type: cross
Abstract: Virtual Reality (VR) applications require robust user identification systems to ensure secure access to equipment and protect worker identities. Motion tracking data from VR headsets and controllers ha…
arXiv:2506.07969v2 Announce Type: replace
Abstract: We consider the problem of modeling high-speed flows using machine learning methods. While most prior studies focus on low-speed fluid flows in which uniform time-stepping is practical, flows approac…
arXiv:2604.15713v1 Announce Type: cross
Abstract: Type annotations are essential when printing terms in a way that preserves their meaning under reparsing and type inference. We study the problem of complete and minimal type annotations for rank-one p…
arXiv:2503.02497v4 Announce Type: replace-cross
Abstract: Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Their application to quantum software development rem…
arXiv:2604.15768v1 Announce Type: cross
Abstract: AI-driven methods have demonstrated considerable success in tackling the central challenge of accurately solving the Schr\”odinger equation for complex many-body systems. Among neural network quantum s…
arXiv:2602.05523v2 Announce Type: replace-cross
Abstract: Agentic large language models (LLMs) are increasingly evaluated on cybersecurity tasks using capture-the-flag (CTF) benchmarks, yet existing pointwise benchmarks offer limited insight into agen…
arXiv:2602.11327v2 Announce Type: replace-cross
Abstract: The rapid development of the AI agent communication protocols, including the Model Context Protocol (MCP), Agent2Agent (A2A), Agora, and Agent Network Protocol (ANP), is reshaping how AI agents…
arXiv:2604.10577v2 Announce Type: replace-cross
Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automate harmful actions programmatically. Existin…