arXiv:2604. 00073v3 Announce Type: replace-cross Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously.
arXiv:2608. 05159v1 Announce Type: new Abstract: Enterprise operations extensively rely on multiple heterogeneous business systems and information applications, which also result in severe data silos and process fragmentation.
arXiv:2605. 10555v2 Announce Type: replace Abstract: As AI agents transition from research prototypes to enterprise production systems, the tool interfaces they consume remain rooted in human-oriented CRUD paradigms.
arXiv:2607. 25076v1 Announce Type: new Abstract: Every major wave of platform software follows the same arc: an initial period of experimentation with competing frameworks and ad-hoc implementations, followed by the articulation of a small set of stable abstractions with well-defined semantics, and finally consolidation around those abstractions into a platform that applications can portably target.
arXiv:2606. 29116v1 Announce Type: new Abstract: Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combine natural language understanding with external services and APIs.
ChatDev 2.0, also called DevAll, is a no-code platform that lets users build, run, and inspect heterogeneous multi‑agent systems (MAS) powered by large language models. It combines a declarative executable graph abstraction with a cycle‑aware execution engine, enabling representation and execution of dynamic, cyclic interactions among diverse agents. The integrated visual interface allows users to author, monitor, and inspect MAS—including human‑in‑the‑loop steps—without writing code, and experiments show it matches state‑of‑the‑art MAS performance across three tasks.
arXiv:2607. 07397v1 Announce Type: new Abstract: Autonomous agents promise substantial gains in speed, scale, and labor efficiency, but their failures can impose abrupt and often irreversible costs.
arXiv:2605. 25160v2 Announce Type: replace Abstract: GUI agents powered by large language models are advancing rapidly, creating urgent needs for evaluation and training based on realistic environments.
arXiv:2606. 07594v1 Announce Type: new Abstract: Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface and offer limited support for user teaching and auditability.
arXiv:2604. 14228v2 Announce Type: replace-cross Abstract: Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user.
arXiv:2505. 21550v2 Announce Type: replace-cross Abstract: Collaborative agentic AI is projected to transform entire industries by enabling AI-powered agents to autonomously perceive, plan, and act within digital environments.
arXiv:2510. 04452v3 Announce Type: replace-cross Abstract: Computer use agents (or "agents") are generative AI that automates actions within user interfaces from user commands.
arXiv:2607. 26300v1 Announce Type: cross Abstract: AI agents are increasingly adept at tackling complex, long-running tasks.