Yilin Xu

[Cyrus (Zikai) Zhou @cyruszzhou]

Excited to share that SatIR has been accepted to COLM 2026! 🎉 Grateful to my incredible collaborators across Stanford and Mayo Clinic. The core idea: for high-stakes retrieval, don't just ask "does this sound relevant?" - ask "is this actually possible?"

Also accepted - DataSTORM from @StanfordOVAL led by @ShichengGLiu , an LLM agent that runs deep research over massive structured databases, turning raw data into coherent analytical narratives (and beating ChatGPT Deep Research): https://t.co/vHY3gGtd9e

[Cyrus (Zikai) Zhou @cyruszzhou]

🔎 In high-stakes domains, a missed search result is not just a search error - it can mean a missed opportunity, delayed decision, or denied service.

Yet most retrieval systems still rank by keywords and embeddings. They can surface candidates that look relevant while missing those that actually satisfy the constraints.

What if an agent could turn those constraints into a retrieval tool that searches for viable options directly?

🌐 Project: https://t.co/sdRZD6QCHt
📄 Paper: https://t.co/GfAg16TI2e

With @Yufei_1001, @kelakexyl, @YuChiangWang1, @ChiehJuChao1, and @MonicaSLam. Grateful to our collaborators across Stanford and Mayo Clinic, and to the broader @stanfordnlp and @StanfordHAI communities that helped shape the environment for this work.

#InformationRetrieval #AIAgents

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