arXiv AI By Mariano Garralda-Barrio

From Task-Guided Conversational Graphs to Goal-Oriented Dialogue Runtimes

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arXiv:2606. 23797v1 Announce Type: cross Abstract: Graph and multi-agent orchestration frameworks make production large language model (LLM) workflows practical, but they do not by themselves solve conversational continuity when users maintain several interdependent objectives.

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EDGE: Engine for Deterministic Graph Evaluation through Conversation Simulation from Graph Structured DSL Configuration

arXiv:2608.29971v1 Announce Type: new Abstract: As agentic systems evolve into complex multi agent orchestration workflows, there is a growing and critical need for systematic frameworks that measure...

By Ram Kulathumani, Regunathan Radhakrishnan, Anupam Tripathi, Xiangbo Mao, Roshanak Omrani, Keshav Somani, Shwet Kamal Mishra, Shayna Lurya
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ChatDev 2.0: A No-Code Multi-Agent Platform for Developing Everything

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.

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