1
LongCat 为 OpenClaw 装上效率引擎：你的自动化任务还能再快 30%
【点评】
依赖第三方订阅进行非官方调用存在账号安全风险与服务不稳定性。为规避此类问题，LongCat 团队提供稳定合规的官方免费 API，开发者可通过官方渠道直接接入 OpenClaw，在确保账号安全的前提下构建自动化工作流。
2
What's involved in getting a "modern" terminal setup?
想拥有现代化终端但被各种配置搞得头大？这篇文章把终端体验拆解得明明白白，从shell到终端模拟器，告诉你每个功能该由谁负责，省去自己瞎琢磨的时间。
Hello! Recently I ran a terminal survey and I asked people what frustrated them. One person commented: There are so many pieces to having a modern ter…
3
Dew Drop – May 11, 2026 (#4665)
每周技术干货合集！从AI辅助编辑器到.NET 11新特性，从本地LLM到微服务模式，帮你快速掌握最新工具和最佳实践，省去到处找资料的时间。
Top Links Build an AI-Powered Rich Text Editor in .NET MAUI with AI AssistView (Tamilarasan Gunasekaran) Getting started with…
4
Claude’s next enterprise battle is not models: it’s the agent control plane
模型之战已是过去式，真正的战场在代理控制层。Anthropic的Claude首次出现在企业编排平台榜单，虽然份额微小，却释放了一个重要信号：下一轮AI企业竞争，拼的是谁掌握AI代理运行的底层基础设施。
New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger figh…
5
Redesign: Everything Broke
选择还在快速迭代的技术框架（比如Astro），就要做好频繁踩坑的准备——每次升级都有可能带来破坏性变更。看似理所当然的进步，对用户来说可能是无穷无尽的折腾。
Okay, so. I spent far too long trying to push my build of Astro via Netlify. Netlify is where I host my site and it automatically detects when a commi…
6
Katy’s Book Bloggin’ Setup
这个自动化书评发布流程绝了！用GitHub action抓取书籍元数据，再通过iOS快捷方式一键发布，解决了手动添加ISBN、图片等繁琐步骤。想写书评又怕麻烦的朋友，这波操作值得偷师。
Dang! I love this automated book review and publish setup by Katy Decorah. She made a GitHub action called read-action to fetch the metadata of a book…
7
Building a UI Kit in Figma
如果你在纠结Figma组件库怎么搭，这篇实操笔记就是你要的。作者把UI Kit拆成四个清晰页面，从入门指南到符号管理，还分享了长期维护的收益——改一个symbol能自动更新上百个组件，省下一天工时。干货满满，设计系统新手和进阶都值得看。
I’ve been working on our UI Kit at Gusto for a couple of months now – this is a project in Figma that lets other designers on our team examine our com…
8
Email is the Magic Key
在社交媒体制造的热闹假象里，email订阅才是真正属于你的忠实读者群。这篇对邮件通讯的深情告白，道破了内容创作者最该珍惜的"魔法钥匙"——不是追逐转瞬即逝的点赞，而是经营一个一个人主动把邮箱交给你的信任网络。
I got to reading this excellent post called How to Make a Book the other day and it’s a collection of advice from writers and novelists about how to g…
9
Greg Brockman: Inside the 72 Hours That Almost Killed OpenAI
OpenAI差点崩盘的72小时，Greg Brockman亲自复盘了Sam Altman被解雇的真相、他为何当天辞职、以及“凤凰”备份公司的诞生。如果你想知道AGI时代最关键的内部博弈和AI对工作的真实冲击，这期干货拉满。
The AI race, the future of AGI, and the inside story of OpenAI. Greg Brockman is the co-founder and President of OpenAI, the company behind ChatGPT an…
10
SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks
工业场景下LLM规划常又长又乱还容易出错？SPIN用DAG+前缀控制强制结构有效，直接省下不必要的工具和API开销，干活利索多了。
arXiv:2605.14051v1 Announce Type: new Abstract: Industrial LLM agent systems often separate planning from execution, yet LLM planners frequently produ…
11
Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations
长对话中，LLM 可能产生看似合理但基于已放弃前提的回复，这给安全带来隐患。这篇文章提出一个线性时间运行时验证器，通过显式依赖图追踪对话前提，有效堵住漏洞。
arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises…
12
Nexus : An Agentic Framework for Time Series Forecasting
时间序列预测不只是数字外推，Nexus用多智能体框架把宏观/微观波动和文本信号整合起来，让LLM的推理能力真正落地到实际预测中。它证明了当前LLM的预测潜力远超以往认知，关键在于如何组织数值和上下文推理。
arXiv:2605.14389v1 Announce Type: new Abstract: Time series forecasting is not just numerical extrapolation, but often requires reasoning with unstruc…
13
OmniDrop: Layer-wise Token Pruning for Omni-modal LLMs via Query-Guidance
全模态大模型被音视频token爆炸拖累？这篇论文提出逐层剪枝策略，从嵌入层深入模型内部，精准剔除冗余token，让高分辨率多模态推理更轻更快。
arXiv:2605.14458v1 Announce Type: new Abstract: Omni-modal large language models have demonstrated remarkable potential in holistic multimodal underst…
14
Deepchecks: Evaluating Retrieval-Augmented Generation (RAG)
评估RAG系统是个老大难，这篇论文直接甩出Deepchecks框架，把检索和生成的复杂关系拆解得明明白白。搞AI落地的人值得一看。
arXiv:2605.14488v1 Announce Type: new Abstract: Large Language Models (LLMs) augmented with Retrieval-Augmented Generation (RAG) techniques are revolu…
15
Cattle Trade: A Multi-Agent Benchmark for LLM Bluffing, Bidding, and Bargaining
大模型会虚张声势、竞价谈判吗？这个新基准把拍卖、暗牌交易、博弈全塞进一个游戏里，测出LLM在复杂经济对抗中经常犯蠢：超价竞拍、自相残杀、破产交易，连对手都摸不清。想看你家AI有多少商业头脑？来试试Cattle Trade。
arXiv:2605.14537v1 Announce Type: new Abstract: We introduce \textsc{Cattle Trade, a multi-agent benchmark for evaluating large language models (LLMs)…
16
AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction
别迷信自己的审美了，AI通过LLM访谈和语义特征提取，在个性化图像美学评估上已经超越人类，甚至比你自己还懂你当下的偏好。这研究深刻挑战了“审美只有人最懂”的认知。
arXiv:2605.14761v1 Announce Type: new Abstract: Accurately predicting individual aesthetic evaluation for images is a fundamental challenge for AI. Va…
17
Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems
当单个AI再强，也难以应对复杂协作任务时，多智能体系统如何避免错误连环放大？这篇综述用LIFE框架把能力基础、协作整合、故障归因与自我进化串成一条因果链，补齐了此前研究各自为战的短板，为构建能自我诊断、自我修复的闭环多智能体系统提供了清晰路线图。
arXiv:2605.14892v1 Announce Type: new Abstract: LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use…
18
Orchard: An Open-Source Agentic Modeling Framework
别被那些闭源智能体框架圈住了，Orchard这个开源框架直接让你在编程、GUI操作、个人助手三个场景上都能训出顶级模型，代码和数据都公开，效果还干翻了不少闭源系统，搞AI智能体的朋友值得试试。
arXiv:2605.15040v1 Announce Type: new Abstract: Agentic modeling aims to transform LLMs into autonomous agents capable of solving complex tasks throug…
19
FaceParts: Segmentation and Editing of Gaussian Splatting
还在为3D人脸编辑头疼？FaceParts直接在Gaussian域无监督分割部件，甚至能跨头像交换胡子眉毛，效果炸裂，还保持了高身份一致性。
arXiv:2605.13853v1 Announce Type: cross Abstract: Facial editing is an important task with applications in entertainment, virtual reality, and digital…
20
AIS: Adaptive Importance Sampling for Quantized RL
用低精度rollout加速RL训练，却引入非平稳偏差，既给探索带来意外好处，又可能导致训练崩溃。这篇论文提出了自适应重要性采样（AIS），动态平衡纠偏与保留探索增益，在数学推理和规划任务上以1.5-2.76倍速度提升匹配全精度基线，是量化RL训练中很实用的方案。
arXiv:2605.13907v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is dominated by the cost of rollout gen…