…View arXiv page View PDF Add to collection Community Struct-Searcher is a training-free agentic workflow that advances multimodal deep research with structure-aware thinking mechanisms. This is an automated message…
…Abstract AgensFlow is an open-source framework that treats multi-agent coordination as an online policy-learning problem under partial observability, enabling learned routing to improve coordination-heavy workflows over static approaches…
…This overlooks a critical real-world requirement of coordinating across multiple applications to accomplish complex profession-specific workflows. To bridge this gap, we present a computer-use benchmark in cross-application workflows…
…AI-generated summary Industrial LLM agent systems often separate planning from execution, yet LLM planners frequently produce structurally invalid or unnecessarily long workflows, leading to brittle failures and avoidable tool and API…
…widely used benchmark s lack sustained performance measurement on real and economically valuable workflows. This paper introduces Agents' Last Exam (ALE), a benchmark designed to evaluate AI agents on long-horizon, economically…
…AI-generated summary Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around these environments remains constrained by the absence of a systematic…
…To further construct reliable instances, MineExplorer uses a multi-agent synthesis workflow that jointly designs task graphs , sandbox scenes , and rule-based milestone evaluators . Human evaluation shows that the multi-agent synthesis…
…the ability to decompose complex tasks, determine when and what to delegate, and integrate returned results into the ongoing workflow. Training data for this capability is scarce in naturally occurring text, and…
…Their workflow is trapped in a repetitive cycle of prompt rewriting for generation refinement, leaving them with no mechanism to directly manipulate the canvas. In essence, the potential of LLMs to serve…
…The combination of high‑level instructions, hardware selection, monitoring, and automation makes the complex process of model training much more approachable, even for developers who may not be ML‑infrastructure experts. I…