Yumin Zhou

Among other things, my team has been focusing on AI research for agents. We just blogged about a recent project: the Test-Time Diffusion Deep Researcher (TTD-DR). This framework uses a Deep Research agent to draft and revise its own drafts using high-quality retrieved information. This approach achieves new state-of-the-art results in writing long-form research reports and completing complex reasoning tasks. The work achieves better results than any other deep research agent we compared to. It also shows that self-evaluation and self-improvement are must-have components of a successful agent. https://lnkd.in/gBZpVMQy

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Excited to share my team's latest work from Google Cloud AI Research (https://lnkd.in/gmejMnn7) on Deep Research (DR) agents! The core challenge with DR agents isn't just analysis—it's generating accurate, coherent, long-form reports. Today, we're introducing Test-Time Diffusion Deep Researcher (TTD-DR), a new framework that fundamentally rethinks this process. Instead of a rigid, linear workflow, TTD-DR mimics human cognition. Here’s how: 🧠 1. Inspired by Humans: It starts with a preliminary draft, then enters iterative cycles of search, reasoning, and revision. 🔄 2. Iterative Refinement (The "Diffusion"): The framework uses a novel "denoising with retrieval" mechanism. The evolving draft itself guides the search for new information, which is then used to refine the draft, step-by-step. 📈 3. Enhanced Quality: A component-wise self-evolution algorithm enhances each part of the workflow, from planning to synthesis. This combined approach achieves state-of-the-art results, including a 74.5% win rate in long-form report generation on the DeepConsult benchmark. This work shows a shift toward iterative, "draft-first" agent design to unlock advanced performance for demanding research tasks. A product version is available on Google Agentspace: https://lnkd.in/g_2QjFgw Read the details: - Google Research Blog: https://lnkd.in/g4XGpqMS - VentureBeat Coverage: https://lnkd.in/gjb9h4yg - Paper: https://lnkd.in/gCpXjd_d Congrats to the incredible team: Rujun Han, Yanfei C., Zoey CuiZhu, Lesly Miculicich, Guan Sun, Yuanjun Bi, Weiming Wen, Hui Wan, Chunfeng Wen, Solène Maître, George Lee, Vishy Tirumalashetty, Yuan (Emily) Xue, Zizhao Zhang, Salem Haykal, Burak Gokturk, Tomas Pfister, and Chen-Yu Lee. #ai #machinelearning #deeplearning #llm #DeepResearch #TestTimeScaling #Diffusion PS. Google Cloud AI Research is hiring both full-time researchers and interns with excellent LLM publication records. Send me your cv directly to [email protected].

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GANs from Ground Up - Simple to Advanced ! I discovered an excellent YouTube playlist that walks through Generative Adversarial Networks step by step, starting from a basic introduction, through building your first simple GAN, and scaling up to DCGAN and WGAN implementations from scratch. Link in comments. #GANs #AIEngineering #GenerativeAI #MachineLearning

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