Semantic Scholar is a free, AI-powered academic search engine and research tool developed by the Allen Institute for AI (AI2). Launched in 2015, the platform indexes over 200 million academic papers across all fields of science, including computer science, biomedical sciences, physics, mathematics, social sciences, and humanities, sourced from publishers, preprint servers, and open access repositories. Semantic Scholar uses natural language processing and machine learning to understand the content and context of academic papers, enabling more intelligent search and discovery than traditional keyword-based academic databases. The platform's key AI features include TLDR summaries that provide one-sentence AI-generated overviews of paper content, semantic search that understands the meaning behind queries to surface relevant papers even when they use different terminology, and citation context analysis that shows how a paper has been cited and in what context by subsequent research. Semantic Scholar also provides the Semantic Reader, an augmented reading interface that enhances the paper reading experience with inline definitions, citation cards, and figure references. The platform generates author profiles with publication histories, citation metrics, h-index calculations, and co-author networks. Its Research Feed feature uses machine learning to recommend new papers based on a user's research interests and reading history. Semantic Scholar offers the Semantic Scholar Academic Graph API, one of the largest open academic knowledge graphs, which researchers and developers can use to build applications on top of the platform's data. The platform is entirely free to use, supported by the Allen Institute for AI as part of its mission to advance AI for the common good. There are no premium tiers or paywalls for any of Semantic Scholar's features.

AI 文档分析

Semantic Scholar 的 Semantic Reader 提供了 AI 驱动的文档分析功能，增强了学术论文的阅读体验。它提供内联术语定义、引文上下文卡片（显示参考论文的相关性）、图表分析和结构导航，帮助读者更高效地理解复杂的学术文档。

AI 知识库

Semantic Scholar 维护着世界上最大的开放学术知识库之一，其 Semantic Scholar Academic Graph 包含超过 2 亿篇论文、引文关系、作者信息和主题分类。这个结构化知识库可通过 API 免费访问，为学术研究工具和应用程序奠定基础。

AI 研究工具

Semantic Scholar 提供了基本的 AI 研究工具，包括智能论文发现、引文上下文分析、作者档案和个性化研究订阅。研究人员使用它来跟踪引文、发现相关工作、识别其领域中的有影响力的论文，以及通过基于其研究兴趣的 AI 驱动推荐来了解新发表的内容。

AI 搜索引擎

Semantic Scholar 是一个领先的 AI 驱动学术搜索引擎，使用自然语言处理来理解研究查询背后的含义，并从包含超过 2 亿篇论文的语料库中获取相关论文。其语义搜索功能超越关键词匹配，可以在所有科学学科中找到概念上相关的研究。

AI 摘要工具

Semantic Scholar 提供了由 AI 生成的 TLDR 摘要，这些摘要提供学术论文的简洁单句概述，使研究人员能够快速评估论文的相关性，而无需阅读完整摘要。该摘要功能适用于其整个包含超过 2 亿篇论文的语料库，极大地加快了文献扫描过程。