Tootfinder

Cardinals' Calais Campbell on mentoring younger players: No point to 'die with all this knowledge' https://www.nfl.com/news/cardinals-calais-campbell-mentoring-younger-players-die-with-all-this-knowledge

NFDI4DS is hosting its second Summer School on Artificial Intelligence and Knowledge Graphs for Scholarly Data (AIKG-SD 2025) 🥳
This year's theme: “Research Towards Sustainable Societies”
🗣 Keynotes & Interactive Tutorials
☕ Networking
🏆 Poster Session & Best Poster Award
September 23/24, 2025
Leuphana University Lüneburg
Application deadline: June 27, 2025!

AIKG-SD 2025
AIKG-SD 2025: Research Towards Sustainable Societies ! Now accepting submissions ! NFDI4DataScience and the AIX Lab at Leuphana University Lüneburg is hosting its second summer school on Artificial Intelligence and Knowledge Graphs for Scholarly Data. Join us for two days of interesting discussions

Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor
Weibo Gao, Qi Liu, Rui Li, Yuze Zhao, Hao Wang, Linan Yre, Fangzhou Yao, Zheng Zhang
https://arxiv.org/abs/2506.11107

Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor
Programming Knowledge Tracking (PKT) aims to dynamically diagnose learners' mastery levels of programming knowledge based on their coding activities, facilitating more effective and personalized programming education. However, current PKT studies primarily focus on the implicit relationship between code content and knowledge assessment, often overlooking two types of noise signals in long-term programming activities: unwanted signals from unrelated submissions and weak signals from minor modifi…

EKPC: Elastic Knowledge Preservation and Compensation for Class-Incremental Learning
Huaijie Wang, De Cheng, Lingfeng He, Yan Li, Jie Li, Nannan Wang, Xinbo Gao
https://arxiv.org/abs/2506.12351

EKPC: Elastic Knowledge Preservation and Compensation for Class-Incremental Learning
Class-Incremental Learning (CIL) aims to enable AI models to continuously learn from sequentially arriving data of different classes over time while retaining previously acquired knowledge. Recently, Parameter-Efficient Fine-Tuning (PEFT) methods, like prompt pool-based approaches and adapter tuning, have shown great attraction in CIL. However, these methods either introduce additional parameters that increase memory usage, or rely on rigid regularization techniques which reduce forgetting but …

Understanding the Effect of Knowledge Graph Extraction Error on Downstream Graph Analyses: A Case Study on Affiliation Graphs
Erica Cai, Brendan O'Connor
https://arxiv.org/abs/2506.12367

Understanding the Effect of Knowledge Graph Extraction Error on Downstream Graph Analyses: A Case Study on Affiliation Graphs
Knowledge graphs (KGs) are useful for analyzing social structures, community dynamics, institutional memberships, and other complex relationships across domains from sociology to public health. While recent advances in large language models (LLMs) have improved the scalability and accessibility of automated KG extraction from large text corpora, the impacts of extraction errors on downstream analyses are poorly understood, especially for applied scientists who depend on accurate KGs for real-wo…

"Pen vs. Keyboard? Why the Tool Doesn’t Matter as Much as You Think for Personal Knowledge Management" #KnowledgeManagement

"Nobody is fired for chosing Microsoft," lautet ein geflügeltes Wort.
Das impliziert aber auch, dass Leute gefeuert werden, die sich gegen die Einführung von #Microsoft-Lösungen stellen. Genai das scheint im Kanton #Luzern dem IT-Sicherheitschef passiert zu sein, wie eine Reportag…

If you want to improve your knowledge of where countries are, and how far apart they are, I can recommend this game… https://globle.org/?

Globle Game - Guess the Country
Play Globle map game! Globle is a game inspired by Wordle and it will test your knowledge of geography. Can you guess the mystery country?

I$^2$S-TFCKD: Intra-Inter Set Knowledge Distillation with Time-Frequency Calibration for Speech Enhancement
Jiaming Cheng, Ruiyu Liang, Chao Xu, Ye Ni, Wei Zhou, Bj\"orn W. Schuller, Xiaoshuai Hao
https://arxiv.org/abs/2506.13127

I$^2$S-TFCKD: Intra-Inter Set Knowledge Distillation with Time-Frequency Calibration for Speech Enhancement
In recent years, complexity compression of neural network (NN)-based speech enhancement (SE) models has gradually attracted the attention of researchers, especially in scenarios with limited hardware resources or strict latency requirements. The main difficulties and challenges lie in achieving a balance between complexity and performance according to the characteristics of the task. In this paper, we propose an intra-inter set knowledge distillation (KD) framework with time-frequency calibrati…

Cardinals' Calais Campbell embracing role as mentor, says he doesn't want his knowledge going 'to a graveyard'

https://www.cbssp…