Tootfinder

❓ Wusstet ihr, dass ihr Metadaten in den Culture Knowledge Graph aufnehmen könnt?
💡 Eine kürzlich erschienene Guideline beschreibt mögliche Integrationswege und bietet grundlegende Hinweise zum Verständnis des Culture Knowledge Graphs.
➡️ Ihr findet die Handreichung in der deutschen und englischen Version auf unserer Knowledge Base:

❓ Wusstet ihr, dass ihr Metadaten in den Culture Knowledge Graph aufnehmen könnt?
💡 Eine kürzlich erschienene Guideline beschreibt mögliche Integrationswege und bietet grundlegende Hinweise zum Verständnis des Culture Knowledge Graphs.
➡️ Ihr findet die Handreichung in der deutschen und englischen Version auf unserer Knowledge Base:

BLOCKS: Blockchain-supported Cross-Silo Knowledge Sharing for Efficient LLM Services
Zhaojiacheng Zhou, Hongze Liu, Shijing Yuan, Hanning Zhang, Jiong Lou, Chentao Wu, Jie Li
https://arxiv.org/abs/2506.21033

BLOCKS: Blockchain-supported Cross-Silo Knowledge Sharing for Efficient LLM Services
The hallucination problem of Large Language Models (LLMs) has increasingly drawn attention. Augmenting LLMs with external knowledge is a promising solution to address this issue. However, due to privacy and security concerns, a vast amount of downstream task-related knowledge remains dispersed and isolated across various "silos," making it difficult to access. To bridge this knowledge gap, we propose a blockchain-based external knowledge framework that coordinates multiple knowledge silos to pr…

Knowledge-Driven Imitation Learning: Enabling Generalization Across Diverse Conditions
Zhuochen Miao, Jun Lv, Hongjie Fang, Yang Jin, Cewu Lu
https://arxiv.org/abs/2506.21057

Knowledge-Driven Imitation Learning: Enabling Generalization Across Diverse Conditions
Imitation learning has emerged as a powerful paradigm in robot manipulation, yet its generalization capability remains constrained by object-specific dependencies in limited expert demonstrations. To address this challenge, we propose knowledge-driven imitation learning, a framework that leverages external structural semantic knowledge to abstract object representations within the same category. We introduce a novel semantic keypoint graph as a knowledge template and develop a coarse-to-fine te…

Domain Knowledge in Requirements Engineering: A Systematic Mapping Study
Marina Ara\'ujo, J\'ulia Ara\'ujo, Romeu Oliveira, Lucas Romao, Marcos Kalinowski
https://arxiv.org/abs/2506.20754

Domain Knowledge in Requirements Engineering: A Systematic Mapping Study
[Context] Domain knowledge is recognized as a key component for the success of Requirements Engineering (RE), as it provides the conceptual support needed to understand the system context, ensure alignment with stakeholder needs, and reduce ambiguity in requirements specification. Despite its relevance, the scientific literature still lacks a systematic consolidation of how domain knowledge can be effectively used and operationalized in RE. [Goal] This paper addresses this gap by offering a com…

Last week, at the #RedIRIS Technical Conference 2025, 400 experts gathered to explore and share knowledge around ICT infrastructure, quantum, AI, Open Science & more.
GÉANT CEO Lise Fuhr was honoured to join as an invited speaker, sharing a message that lies at the core of our NREN community:
“It’s all about collaboration and knowledge sharing. These are key components of how we m…

Jornadas Técnicas de RedIRIS 2025

ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
Mina Namazi, Alexander Nemecek, Erman Ayday
https://arxiv.org/abs/2506.20915

ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
As the deployment of large language models (LLMs) grows in sensitive domains, ensuring the integrity of their computational provenance becomes a critical challenge, particularly in regulated sectors such as healthcare, where strict requirements are applied in dataset usage. We introduce ZKPROV, a novel cryptographic framework that enables zero-knowledge proofs of LLM provenance. It allows users to verify that a model is trained on a reliable dataset without revealing sensitive information about…

We're recruiting on our MSc Sociology and Data Analytics for next September at the University of Limerick @…

This MSc offers in depth knowledge of sociological analysis, research… | Faculty of Arts, Humanities and Social Sciences, University of Limerick
This MSc offers in depth knowledge of sociological analysis, research methods and social science analytics - including high level training in data, data science, and data mining, and a range of sequenced topics that include crime, law, and deviance, culture and media, health and well-being, political analysis and social movements, and stratification and social inequality. The combination of high level training in research methods and robust exposure to core topics in Sociology and the Social …

Object knowledge representation in the human visual cortex requires a connection with the language system https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003161 "Our experiments reveal the contribution of the vision-la…

Object knowledge representation in the human visual cortex requires a connection with the language system
This study shows that communication between the visual cortex and the brain language system is necessary for the representation of object knowledge in the visual cortex and for corresponding behaviors in humans. This highlights the significance of connections between sensory and language systems for object knowledge in the human brain.

Generating Reliable Adverse event Profiles for Health through Automated Integrated Data (GRAPH-AID): A Semi-Automated Ontology Building Approach
Srikar Reddy Gadusu, Larry Callahan, Samir Lababidi, Arunasri Nishtala, Sophia Healey, Hande McGinty
https://arxiv.org/abs/2506.20851

Generating Reliable Adverse event Profiles for Health through Automated Integrated Data (GRAPH-AID): A Semi-Automated Ontology Building Approach
As data and knowledge expand rapidly, adopting systematic methodologies for ontology generation has become crucial. With the daily increases in data volumes and frequent content changes, the demand for databases to store and retrieve information for the creation of knowledge graphs has become increasingly urgent. The previously established Knowledge Acquisition and Representation Methodology (KNARM) outlines a systematic approach to address these challenges and create knowledge graphs. However,…