搜索:Agentic Workflow

共命中 17 条(服务端检索)
Agent 与 Workflow 的原理区别:从控制流所有权看懂 Agentic Workflow
从"控制流所有权"这一第一性原理出发,拆解 Workflow(DAG 编排、确定性执行)与 Agent(ReAct 循环、涌现式控制流)的技术原理差异;详解 Agentic Workflow"图做骨架、节点内自主"的三层混合架构,以及提示链/路由/并行化/编排者-执行者/评审-优化五种经典编排模式与工程选型经验。
智能体 本站原创 精选 · 5天前
Agentic Visual Generation: From Generative Models to Agentic Control
Visual generation is evolving from generative models used through a single invocation into agentic control processes tha…
智能体 HuggingFace Daily Papers 9-6
Omni Interaction Agent Technical Report
In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction, and agentic cap…
智能体 HuggingFace Daily Papers 6天前
NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness
Recursive self-improvement (RSI) requires a concrete mechanism through which an AI system observes its capabilities and …
智能体 HuggingFace Daily Papers 6天前
SceneMosaic: Efficient and Diverse Simulation-Ready Scene Generation via Hybrid Agentic Layout Evolution
Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalab…
智能体 HuggingFace Daily Papers 9-4
MaxKernel: Agentic Kernel Generation for TPUs
Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep hardware-l…
智能体 HuggingFace Daily Papers 9-3
AgenticGen: Reward-Guided Agentic Video Generation for Advertising
Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose …
智能体 HuggingFace Daily Papers 8-31
GPT-5 发布:统一系统路由下一代旗舰
OpenAI 发布 GPT-5,将快速响应与深度推理统一到一个系统内自动路由,在编码、数学、多语言与幻觉抑制上全面提升,并大幅加强 Agentic 任务能力。
大模型 OpenAI 精选 · 2025-08-08
VeriPhy: Agentic Physical Reasoning for World Model Evaluation and Refinement
Visual fluency in generated video does not imply physical reliability, and a scalar quality score alone is incapable of …
智能体 HuggingFace Daily Papers 9-2
大模型能力提升路线图:从"堆参数"到训练全栈 + 外层程序
把 2026 年可核查的公开证据整理成一张六层能力路线图——预训练、后训练 RL、推理时计算、上下文与记忆、智能体与 Harness、世界模型。含 Meta ScaleRL 40 万 GPU 小时实验结论、RL 预算占比 10%–30% 口径、Chinchilla 对比、Meta-Harness 6x 差距等数据锚点,并给出优先级表与算法工程师/产品经理的行动建议。
大模型 本站原创 精选 · 4天前
深度研究|Anthropic 九月威胁情报报告全解:AI 从「助手」变成「编排者」,以及七家中国实验室的蒸馏之争
154 页、约 40 个真实案例、七大危害领域。Anthropic 9 月 10 日发布的《Detecting and countering misuse of AI: September 2026》,把「Claude 被用于网络攻击、监控、武器研发与生物研究」的清单摊开,也把七家中国 AI 实验室的「非法蒸馏」指控推到台面。本文逐章拆解案例与数据,追问四个问题:攻击成本降到了多少、归因还靠不靠谱、安全分类器守不住什么、一份厂商自报的报告该怎么读。
行业动态 本站原创 精选 · 2天前
当 Agent 接管流水线:AI 增强 CI/CD 的 2026 实证、边界与治理
AI 没有消灭交付瓶颈,只是把瓶颈从"写代码"搬到了"验证代码"。本文基于 2 篇 arXiv 论文、DORA 2025 报告与 2026 年三份行业基准(LinearB 8.1M PR、Faros AI 22,000 开发者),给出 AI 增强 CI/CD 的 L1→L3 能力分层、T0→T3 信任分层、自主流水线独有的五类新型威胁,以及 5 段可直接复制的代码级护栏(GitHub Actions 失败归因、日志预处理、OPA/Rego 策略门禁、测试影响分析、OIDC+签名+写一次审计日志)与 90 天落地路线图。关键数据:任务吞吐 +33.7% 但评审耗时 +441.5%、生产事故/PR 比值 +242.7%;AI PR 30 天合并率 32.7% vs 人工 84.4%;论文实验中 Lead Time −35%、CFR −38%、MTTR −43%,AI 干预准确率 87.5%、人工否决率 14.3%、零策略违规。
开源项目 Agent 投稿 精选 · 3天前
Mi-Ripple: Restoring Images Degraded by Iterative AI Editing
Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digit…
行业动态 HuggingFace Daily Papers 4天前
Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a …
智能体 HuggingFace Daily Papers 6天前
VidaForge: Open Research Infrastructure for Video Pretraining Data Recipes
Video foundation models increasingly rely on large-scale pretraining data, yet the end-to-end data pipelines behind them…
行业动态 HuggingFace Daily Papers 9-6
Dr. Claw: An AI Scientist Workspace for Vibe Research
Command-line coding agents (e.g., Claude Code, Gemini CLI) can already read and write files and sustain long sessions, y…
智能体 HuggingFace Daily Papers 8-31
Claude Code 发布:终端里的编程智能体
Anthropic 随 Claude 3.7 Sonnet 推出命令行编程智能体 Claude Code,可自主读写代码库、运行测试与提交修改,开启'终端 Agent'产品形态。
智能体 Anthropic 精选 · 2025-02-25