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阿里杀进Agent上下文战场：钉钉聊天、企业文档、工作数据终于要被Agent吃进去了
阿里出手补齐Agent数据加工层，钉钉聊天、企业文档和业务数据统一变成上下文，让AI真正融入工作流。
MyContext补上Agent的数据加工层
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ContextMemory v0.1.0-beta: what shipped
Agent memory 新玩法：像维基百科一样可浏览的 AI 记忆，告别向量黑盒与 RAG 注入，还新增 Cursor 风格 HTTP、视觉、PDF 等 Agent 工具。
ContextMemory v0.1.0-beta is out. Agent memory you can open like a wiki — not a vector black box, not classic RAG inject. Release notes ## 0.1.0-beta…
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Agents explained, what makes an LLM an agent?
从工具调用到上下文管理，深度拆解LLM agent的核心机制与实现策略
Article URL: https://raw.githubusercontent.com/langens-jonathan/blog/refs/heads/main/20260729_AgentsDefined_Part1of3 Comments URL: https://news.ycombi…
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Context Tuning for In-Context Optimization
ICML 2026最新论文，提出上下文调优方法，让大模型在上下文优化中表现更高效。
arXiv:2507.04221v3 Announce Type: replace-cross Abstract: We introduce Context Tuning, a simple and effective method to significantly enhance few-shot…
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ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning
长上下文推理新突破，递归证据回放让LLM精准捕捉关键信息
arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large langua…
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Persistent memory for AI agents is three problems, not one
拆解AI Agent持久记忆的三层架构，揭示缺失确定性语境治理的隐患。
Article URL: https://promptowl.ai/resources/persistent-memory-ai-agents/ Comments URL: https://news.ycombinator.com/item?id=48747378 Points: 1 # Comme…
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Context intelligence for your data and AI agents at scale
AWS推出基于Apache Iceberg开放格式的上下文智能层，为数据和AI代理提供规模化、无基础设施开销的元数据服务。
Article URL: https://aws.amazon.com/blogs/machine-learning/context-intelligence-for-your-data-and-ai-agents-at-scale/ Comments URL: https://news.ycomb…
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Revisiting the Systematicity in Negation in the Era of In-Context Learning
探究大模型在上下文学习中对否定表达的系统性处理能力，揭示新发现与挑战
arXiv:2606.16867v1 Announce Type: new Abstract: Understanding the meaning of negated sentences remains one of the challenges for language models, even…
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Show HN: theta_py, bindings to the Theta CLI
为Theta CLI提供Python绑定，让你在代码中直接调用AI命令行工具，提升开发效率。
Article URL: https://github.com/tamarillo-ai/theta_py Comments URL: https://news.ycombinator.com/item?id=48514641 Points: 1 # Comments: 0
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In-Context Graphical Inference
新的上下文图推理范式，无需参数更新即可在图中实现快速预测与结构归纳。
arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: e…
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Learning without training: The implicit dynamics of in-context learning
不做梯度更新也能学习？这篇论文揭示了上下文学习背后的隐式动力学机制
arXiv:2507.16003v4 Announce Type: replace Abstract: One of the most striking features of Large Language Models (LLMs) is their ability to learn in-con…
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Best MCP Servers for AI Coding in 2026: The 7 Worth Installing in Cursor, Claude Code, and Windsurf
2026年AI编码必装的7个MCP服务器，Context7+GitHub MCP组合覆盖90%工作流，Cursor/Claude Code/Windsurf用户必看。
This article was originally published on aicoderscope.com The verdict up front: Context7 and GitHub MCP belong in every setup. Add Playwright if you w…
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Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval
ACL 2026新研究，用分布外数据代理解决目标不可访问时的上下文示例检索，显著增强大模型ICL鲁棒性。
arXiv:2606.00014v1 Announce Type: cross Abstract: Although studies have demonstrated that Large Language Models (LLMs) can perform well on Out-of-Dist…
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Prompting styles - Basic
一文快速掌握五种基础提示风格，零基础也能精准操控大模型输出。
Query which we ask the LLM is referred to as prompt. The way in which we provide prompt to LLM makes a difference and there are different ways to to p…
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Best MCP Memory Servers for Teams in 2026: Context Cloud vs mem0 vs Basic Memory vs claude-mem vs MemPalace
2026年团队级MCP内存服务器横向评测，五大方案（Context Cloud、mem0等）优劣势全解析，助你选对AI记忆方案。
There are now dozens of MCP memory servers. I've tried most of them. They almost all solve the same problem: your AI forgets everything between sessio…
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CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning
提出CurveRL方法，通过分布感知的上下文重加权提升LLM推理性能，理论严谨效果显著。
arXiv:2605.24331v1 Announce Type: new Abstract: Context or prompt-level reweighting has emerged as a central algorithmic lever in Reinforcement Learni…
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Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis
Context-CoT通过高质量推理合成增强上下文学习，为AI大模型提供更优的示例生成策略。
arXiv:2605.25354v1 Announce Type: new Abstract: While LLMs excel at reasoning over prompts using static pretrained knowledge, they struggle significan…
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MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics
为阿尔茨海默症辅助机器人量身定制，融合上下文学习与微调的LLM个性化方案
arXiv:2605.23941v1 Announce Type: new Abstract: Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and langu…
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Context: Proactive Goal-Directed Intelligence via Composable Sandboxed Programs, Declarative Wiring, and Structured Interaction
提出Context智能层架构，通过沙盒程序、声明式连接与结构化交互实现主动目标导向智能。
arXiv:2605.23928v1 Announce Type: new Abstract: We present Context, the intelligence layer of the Magarshak Architecture, which replaces reactive quer…
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Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
从形式语言学习视角，剖析微调与上下文学习的根本差异，ACL 2026 重磅论文。
arXiv:2604.23267v2 Announce Type: replace-cross Abstract: Large language models (LLMs) operate in two fundamental learning modes - fine-tuning (FT) an…