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-- 基于本期点赞/点踩的读者反馈。AI Radar
AI 技术雷达
把每日值得读的 AI 工程、模型、智能体、产品化资讯归档成期刊。先看精选，再翻往期。Current Issue
2026-10-28
本期收录 4 篇 AI 技术资讯，0 篇被标记为精选。主要来源包括 arXiv AI/ML(2)、Google DeepMind(1)、IEEE Spectrum AI(1)，本期技术主题包括 检索增强生成。Featured
0 被人工或规则标记为值得优先阅读。Sources
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Google DeepMind
Genie 4: A new generation of world simulation
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.IEEE Spectrum AI
I Used AI to Fake a Scientific Paper. Here’s What Happened
Science has a spam problem. And the spam filter is getting clogged up. According to all reports, academic publishing is drowning in what has come to be called AI slop: low-quality, mass-produced content generated with AI. By 2025, an estimated 57 percent of all published academic articles exhibited detectable evidence of large language model (LLM) influence, a massive jump from 12 percent in 2023. What’s more, over 12 percent of Nature Communications reviews were found to be completely AI-generated in 2025. Given that for every 40 papers showing statistical evidence of AI usage in 2025, only oarXiv AI/ML
Retriever-Free Retrieval: Navigating Documents with Decision Models
While language models have become dramatically more capable, retrieval still largely relies on lexical matching or similarity in fixed embedding spaces. This creates a capability asymmetry: what the retriever fails to find, even the strongest generator cannot recover. We propose DecisionRAG, which brings the capabilities of pretrained language models to retrieval using decision models that jointly evaluate candidate branches in a single forward pass, without generating any tokens, and show that judging candidates in a shared context makes their relevance estimates comparable. Like a person broarXiv AI/ML