knowledge graph
PulseAugur coverage of knowledge graph — every cluster mentioning knowledge graph across labs, papers, and developer communities, ranked by signal.
- 2026-05-19 research_milestone A new paper proposes a framework for inferring and defending against sensitive attribute inference from knowledge graph embeddings. 来源
10 天有情绪数据
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AI联合临床医生利用知识图谱将诊断错误减少30%
一个由知识图谱驱动的AI联合临床医生系统将于2026年彻底改变医疗随访和决策支持。该技术旨在提高诊断准确性并实现个性化患者护理，研究表明诊断错误可能减少30%。该AI旨在成为临床决策中的平等伙伴，改善患者预后并减轻医生工作负担。
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OntoLogX uses LLMs to extract actionable threat intelligence from cybersecurity logs
Researchers have developed OntoLogX, an AI agent designed to extract Cyber Threat Intelligence (CTI) from raw cybersecurity logs. The system utilizes Large Language Models (LLMs) combined with a lightweight log ontology…
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Researchers build knowledge graphs from sparse autoencoder features for model interpretability
Researchers have developed a method to transform sparse autoencoder (SAE) features into structured knowledge graphs. This process involves creating a domain-specific concept universe from SAE features and then building …
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Researchers develop new methods for knowledge graph retrieval and completion
Researchers have developed new frameworks to enhance knowledge graph completion and visual question answering by integrating multimodal knowledge graphs with retrieval-augmented generation techniques. One approach, RADD…
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New models improve LLM reasoning evaluation and control over internal states
Researchers have developed a new framework to minimize "collateral damage" in activation steering for large language models (LLMs), which aims to control model behavior without negatively impacting performance on unrela…
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STEM framework enhances knowledge graph reasoning with structure-tracing evidence mining
Researchers have introduced STEM, a new framework designed to enhance knowledge graph-based question answering. This approach tackles challenges related to the structural heterogeneity of knowledge graphs and the lack o…
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Study reveals catastrophic forgetting in knowledge graph embeddings is underestimated
Researchers have identified a significant issue in evaluating Continual Knowledge Graph Embedding (CKGE) methods, termed 'entity interference.' This phenomenon occurs when new entities introduced into a knowledge graph …