544 citations · 561 across the 16 of their papers we have counts for
17 papers
Mapping the Landscape of Open Access Dashboards -- A Dataset for Research and Infrastructure Development
Johannes Schneider, Heinz Pampel
As Open Access continues to gain importance in science policy, understanding the proportion of Open Access publications relative to the total research output of research-performing…
Generative human motion mimicking through feature extraction in denoising diffusion settings
Alexander Okupnik, Johannes Schneider, Kyriakos Flouris
Recent success with large language models has sparked a new wave of verbal human-AI interaction. While such models support users in a variety of creative tasks, they lack the embod…
AI Exchange Platforms
Johannes Schneider, Rene Abraham
The rapid integration of Artificial Intelligence (AI) into organizational technology frameworks has transformed how organizations engage with AI-driven models, influencing both ope…
Thematic and Task-Based Categorization of K-12 GenAI Usages with Hierarchical Topic Modeling
Johannes Schneider, Béatrice S. Hasler, Michaela Varrone +4
We analyze anonymous interaction data of minors in class-rooms spanning several months, schools, and subjects employing a novel, simple topic modeling approach. Specifically, we ca…
Focus on Likely Classes for Test-Time Prediction
Johannes Schneider
We ask: Can focusing on likely classes of a single, in-domain sample improve accuracy? Prior work argued "no", we answer "yes" on average. Standard entropy minimization yields larg…
Generative to Agentic AI: Survey, Conceptualization, and Challenges
Johannes Schneider
Agentic AI builds upon Generative AI (GenAI). It constitutes the next major step in the evolution of AI with much stronger reasoning, learning, and interaction capabilities that en…
Using Phonemes in cascaded S2S translation pipeline
Rene Pilz, Johannes Schneider
This paper explores the idea of using phonemes as a textual representation within a conventional multilingual simultaneous speech-to-speech translation pipeline, as opposed to the…
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis +4
Concept-based models are an emerging paradigm in deep learning that constrains the inference process to operate through human-interpretable variables, facilitating explainability a…
Improving Next Tokens via Second-to-Last Predictions with Generate and Refine
Johannes Schneider
Autoregressive language models like GPT aim to predict next tokens, while autoencoding models such as BERT are trained on tasks such as predicting masked tokens. We train a decoder…
Empowering Clients -- Transformation of Design Processes Due to Generative AI
Johannes Schneider, Kilic Sinem, Daniel Stockhammer
Generative AI (GenAI) is transforming creative fields shaping our culture and our heritage. We focus on widespread interactions between clients and (creative) specialists highlight…
Topic Modeling with Fine-tuning LLMs and Bag of Sentences
Johannes Schneider
Large language models (LLMs) are increasingly used for topic modeling, outperforming classical topic models such as LDA. Commonly, pre-trained LLM encoders such as BERT are used ou…
What comes after transformers? -- A selective survey connecting ideas in deep learning
Johannes Schneider
Transformers have become the de-facto standard model in artificial intelligence since 2017 despite numerous shortcomings ranging from energy inefficiency to hallucinations. Researc…
Exploring Human-LLM Conversations: Mental Models and the Originator of Toxicity
Johannes Schneider, Arianna Casanova Flores, Anne-Catherine Kranz
This study explores real-world human interactions with large language models (LLMs) in diverse, unconstrained settings in contrast to most prior research focusing on ethically trim…
Embracing the Enemy
Álvaro Delgado-Vega, Johannes Schneider
A principal can partially influence the allocation of power between two competing parties. The principal is closer to one party, the ``friend'', than to the other, the ``enemy''. T…
Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda
Johannes Schneider
Generative AI (GenAI) marked a shift from AI being able to recognize to AI being able to generate solutions for a wide variety of tasks. As the generated solutions and applications…
Understanding and Leveraging the Learning Phases of Neural Networks
Johannes Schneider, Mohit Prabhushankar
The learning dynamics of deep neural networks are not well understood. The information bottleneck (IB) theory proclaimed separate fitting and compression phases. But they have sinc…
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Luca Longo, Mario Brcic, Federico Cabitza +16
As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In respo…