<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>推理 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E6%8E%A8%E7%90%86/</link><description>Recent content in 推理 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:37:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E6%8E%A8%E7%90%86/index.xml" rel="self" type="application/rss+xml"/><item><title>大模型思维链推理：CoT技术演进与未来方向</title><link>https://guijiagi.com/posts/b1-acff1ec2/</link><pubDate>Thu, 16 Jul 2026 11:37:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-acff1ec2/</guid><description>系统梳理思维链推理技术的发展，从基础CoT到Tree of Thoughts再到推理时Scaling</description></item><item><title>Prompt工程进阶：思维链到思维树的演进</title><link>https://guijiagi.com/posts/article-18/</link><pubDate>Sun, 12 Jul 2026 19:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-18/</guid><description>从CoT到ToT再到GoT，系统梳理Prompt工程中思维结构化的技术演进和实践方法</description></item><item><title>Prompt工程进阶：思维链到思维树的演进</title><link>https://guijiagi.com/posts/b2-e84f5637/</link><pubDate>Sun, 12 Jul 2026 19:50:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-e84f5637/</guid><description>从CoT到ToT再到GoT，系统梳理Prompt工程中思维结构化的技术演进和实践方法</description></item><item><title>思维链2026进阶技巧：让AI真正学会思考</title><link>https://guijiagi.com/posts/chain-of-thought-2026-advanced/</link><pubDate>Thu, 02 Jul 2026 11:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/chain-of-thought-2026-advanced/</guid><description>2026年思维链（Chain-of-Thought）提示工程进阶技巧与最佳实践</description></item><item><title>神经符号AI 2026：融合两条路线</title><link>https://guijiagi.com/posts/neuro-symbolic-ai-2026/</link><pubDate>Thu, 02 Jul 2026 10:38:00 +0800</pubDate><guid>https://guijiagi.com/posts/neuro-symbolic-ai-2026/</guid><description>神经网络与符号AI的融合：2026年的最新进展</description></item><item><title>Chain-of-Thought 进阶：Tree-of-Thought 与 Graph-of-Thought</title><link>https://guijiagi.com/posts/chain-of-thought-advanced-tot-got/</link><pubDate>Sun, 28 Jun 2026 10:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/chain-of-thought-advanced-tot-got/</guid><description>深入解析 CoT 的进化路线——Tree-of-Thought 与 Graph-of-Thought 推理框架，附代码实现与效果对比</description></item><item><title>Chain-of-Thought提示工程进阶</title><link>https://guijiagi.com/posts/chain-of-thought-advanced/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/chain-of-thought-advanced/</guid><description>从基础CoT到高级变体的全面指南，掌握思维链提示工程的进阶技巧</description></item><item><title>Hermes推理能力评测</title><link>https://guijiagi.com/posts/hermes-reasoning-capability/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/hermes-reasoning-capability/</guid><description>Hermes推理能力评测</description></item><item><title>KV Cache优化策略详解</title><link>https://guijiagi.com/posts/kv-cache-optimization/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/kv-cache-optimization/</guid><description>KV Cache优化策略详解</description></item><item><title>SGLang推理框架解析</title><link>https://guijiagi.com/posts/sglang-inference-framework/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/sglang-inference-framework/</guid><description>SGLang推理框架解析</description></item><item><title>vLLM开源推理引擎</title><link>https://guijiagi.com/posts/vllm-opensource-inference/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-opensource-inference/</guid><description>vLLM开源推理引擎</description></item><item><title>思维链变体对比分析</title><link>https://guijiagi.com/posts/cot-variants-comparison/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/cot-variants-comparison/</guid><description>Zero-shot CoT、Few-shot CoT、Auto-CoT等思维链变体的深度对比与选型指南</description></item><item><title>推理时计算Scaling Laws</title><link>https://guijiagi.com/posts/inference-scaling-laws/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/inference-scaling-laws/</guid><description>推理时计算Scaling Laws</description></item><item><title>Prompt 链式设计：从简单到复杂的推理阶梯</title><link>https://guijiagi.com/posts/prompt-chain-design/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/prompt-chain-design/</guid><description>系统讲解 Prompt 链式设计的原理、模式与工程实践，构建从简单推理到复杂任务分解的完整方法论</description></item><item><title>ReAct vs Plan-and-Execute：智能体推理范式对比</title><link>https://guijiagi.com/posts/react-vs-plan-execute/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/react-vs-plan-execute/</guid><description>深入对比 ReAct 与 Plan-and-Execute 两种主流智能体推理范式的工作原理、优劣势及适用场景，指导工程选型。</description></item><item><title>AI 推理服务架构：从单机到分布式弹性扩展</title><link>https://guijiagi.com/posts/ai-inference-serving/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-inference-serving/</guid><description>系统讲解 AI 推理服务的架构演进，涵盖模型加载、批处理、GPU 调度与弹性伸缩</description></item><item><title>Chain of Thought 精通：从零到推理增强</title><link>https://guijiagi.com/posts/chain-of-thought-mastery/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/chain-of-thought-mastery/</guid><description>深入解析 Chain of Thought 提示技术，从基础概念到高级变体，全面掌握 CoT 推理增强的实践方法。</description></item><item><title>SGLang 探理引擎：结构化生成的高性能方案</title><link>https://guijiagi.com/posts/sglang-inference/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/sglang-inference/</guid><description>深入解析 SGLang 推理引擎的核心技术原理、性能优势与生产部署实践，涵盖 RadixAttention、结构化生成、并发处理等关键特性。</description></item><item><title>vLLM 生产部署指南：高吞吐推理引擎</title><link>https://guijiagi.com/posts/vllm-production-guide/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-production-guide/</guid><description>从架构原理到生产部署，全面解析 vLLM 高吞吐推理引擎的核心技术、性能调优与运维方案。</description></item><item><title>连续批处理：vLLM 高吞吐推理的核心技术</title><link>https://guijiagi.com/posts/continuous-batching/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/continuous-batching/</guid><description>深度解析 vLLM 连续批处理（Continuous Batching）如何通过动态请求调度和 PagedAttention 实现高吞吐 LLM 推理服务。</description></item><item><title>推理模型深度对比：o1 vs o3 vs Claude Thinking vs DeepSeek-R1</title><link>https://guijiagi.com/posts/reasoning-model-deep/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/reasoning-model-deep/</guid><description>深度对比 2026 年四大推理模型：OpenAI o1/o3、Claude Thinking、DeepSeek-R1 在数学竞赛、逻辑推理、代码生成中的表现与思维链可读性分析。</description></item><item><title>SGLang vs vLLM：新一代推理引擎之争</title><link>https://guijiagi.com/posts/sglang-vs-vllm/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/sglang-vs-vllm/</guid><description>从 RadixAttention 到缓存共享，深度对比 SGLang 与 vLLM 的架构差异、性能表现与适用场景。</description></item><item><title>Text Generation Inference 评测：HuggingFace 的推理服务器</title><link>https://guijiagi.com/posts/text-generation-webui/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/text-generation-webui/</guid><description>深入评测 TGI 架构、Flash Attention 集成、Continuous Batching、量化支持及与 vLLM 的全面对比。</description></item><item><title>ReAct Prompt 模式：推理与行动的交织</title><link>https://guijiagi.com/posts/react-prompt-pattern/</link><pubDate>Wed, 24 Jun 2026 16:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/react-prompt-pattern/</guid><description>深入解析 ReAct 模式的 Thought-Action-Observation 循环、工具调用集成与代码实现</description></item><item><title>Self-Consistency 技巧：多次采样提升推理质量</title><link>https://guijiagi.com/posts/self-consistency-guide/</link><pubDate>Wed, 24 Jun 2026 16:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/self-consistency-guide/</guid><description>深入解析 Self-Consistency 技术，通过多次采样与多数投票显著提升 LLM 推理质量</description></item><item><title>vLLM 高级配置指南：压榨每一滴性能</title><link>https://guijiagi.com/posts/vllm-advanced-guide/</link><pubDate>Wed, 24 Jun 2026 16:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vllm-advanced-guide/</guid><description>深入 vLLM 高级配置，从 PagedAttention 到张量并行、量化推理与 LoRA 动态加载</description></item><item><title>推测解码加速原理：Draft Model 验证范式</title><link>https://guijiagi.com/posts/speculative-decoding/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/speculative-decoding/</guid><description>深入解析推测解码如何通过 Draft Model 并行验证加速 LLM 自回归推理</description></item><item><title>思维链 Prompt 工程指南：让 LLM 学会一步步思考</title><link>https://guijiagi.com/posts/chain-of-thought-guide/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/chain-of-thought-guide/</guid><description>深入解析思维链（Chain-of-Thought）Prompt 工程技术，涵盖 Zero-shot CoT、Few-shot CoT、Self-Consistency、Tree-of-Thought 与 Graph-of-Thought 的原理、对比与实战。</description></item></channel></rss>