RAG / 检索增强生成

RAG-Enhanced Kernel-Based Heuristic Synthesis (RKHS): A Structured Methodology Using Large Language Models for Hardware Design

基于检索增强的核启发式合成（RKHS）：利用大语言模型的结构化方法用于硬件设计

Shiva Ahir, Alex Doboli

专题命中 图谱与结构化RAG ：RAG(title,abstract)；retrieval-augmented generation(abstract)；分类 cs.IR

AI总结 本文提出RKHS方法，结合检索增强生成、紧凑核启发式模板和LLM驱动的反馈循环，用于硬件设计中的启发式优化，实验证明其在降低延迟的列表调度中有效。

Comments Presented at the NSF Workshop on Agents for Chip Design Automation, UCLA

Deterministic Legal Agents: A Canonical Primitive API for Auditable Reasoning over Temporal Knowledge Graphs

确定性法律代理：用于可审计时间知识图谱推理的规范性原始API

Hudson de Martim

机构 * Federal Senate of Brazil（巴西联邦议会） 纠错

专题命中 图谱与结构化RAG ：RAG(abstract,abstract_cn)；retrieval-augmented generation(abstract)；分类 cs.IR、cs.CL、cs.AI

AI总结 本文提出SAT-Graph API，通过确定性符号子系统与概率语言模型交互，实现法律领域可审计的时间知识图谱推理，将单次检索生成改为主动推理-行动-观察流程。

Comments Substantially revised version consolidating the paper as a formal SAT-Graph API specification: clarifies Probability Isolation and post-anchoring determinism, broadens semantic anchoring to open and thematic legal queries, refines the data models and temporal primitives, and strengthens the use cases, limitations, and bibliography