33 citations · 61 across the 42 of their papers we have counts for
15 papers · 1 filter
Challenges and Opportunities for Visual Analytics in Jurisprudence
Daniel Fürst, Mennatallah El-Assady, Daniel A. Keim +1
Legal exploration, analysis, and interpretation remain complex and demanding tasks, even for experienced legal scholars, due to the domain-specific language, tacit legal concepts,…
Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework
Yannick Metz, David Lindner, Raphaël Baur +1
Reinforcement Learning from Human feedback (RLHF) has become a powerful tool to fine-tune or train agentic machine learning models. Similar to how humans interact in social context…
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities
Kenza Amara, Lukas Klein, Carsten Lüth +3
The various limitations of Generative AI, such as hallucinations and model failures, have made it crucial to understand the role of different modalities in Visual Language Model (V…
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
Lukas Klein, Carsten T. Lüth, Udo Schlegel +3
Explainable AI (XAI) is a rapidly growing domain with a myriad of proposed methods as well as metrics aiming to evaluate their efficacy. However, current studies are often of limit…
iToT: An Interactive System for Customized Tree-of-Thought Generation
Alan Boyle, Isha Gupta, Sebastian Hönig +4
As language models have become increasingly successful at a wide array of tasks, different prompt engineering methods have been developed alongside them in order to adapt these mod…
iNNspector: Visual, Interactive Deep Model Debugging
Thilo Spinner, Daniel Fürst, Mennatallah El-Assady
Deep learning model design, development, and debugging is a process driven by best practices, guidelines, trial-and-error, and the personal experiences of model developers. At mult…
ProvenanceWidgets: A Library of UI Control Elements to Track and Dynamically Overlay Analytic Provenance
Arpit Narechania, Kaustubh Odak, Mennatallah El-Assady +1
We present ProvenanceWidgets, a Javascript library of UI control elements such as radio buttons, checkboxes, and dropdowns to track and dynamically overlay a user's analytic proven…
MelodyVis: Visual Analytics for Melodic Patterns in Sheet Music
Matthias Miller, Daniel Fürst, Maximilian T. Fischer +3
Manual melody detection is a tedious task requiring high expertise level, while automatic detection is often not expressive or powerful enough. Thus, we present MelodyVis, a visual…
On Affine Homotopy between Language Encoders
Robin SM Chan, Reda Boumasmoud, Anej Svete +8
Pre-trained language encoders -- functions that represent text as vectors -- are an integral component of many NLP tasks. We tackle a natural question in language encoder analysis:…
Challenges and Opportunities in Text Generation Explainability
Kenza Amara, Rita Sevastjanova, Mennatallah El-Assady
The necessity for interpretability in natural language processing (NLP) has risen alongside the growing prominence of large language models. Among the myriad tasks within NLP, text…
Understanding Large Language Model Behaviors through Interactive Counterfactual Generation and Analysis
Furui Cheng, Vilém Zouhar, Robin Shing Moon Chan +3
Understanding the behavior of large language models (LLMs) is crucial for ensuring their safe and reliable use. However, existing explainable AI (XAI) methods for LLMs primarily re…
Deconstructing Human-AI Collaboration: Agency, Interaction, and Adaptation
Steffen Holter, Mennatallah El-Assady
As full AI-based automation remains out of reach in most real-world applications, the focus has instead shifted to leveraging the strengths of both human and AI agents, creating ef…
generAItor: Tree-in-the-Loop Text Generation for Language Model Explainability and Adaptation
Thilo Spinner, Rebecca Kehlbeck, Rita Sevastjanova +4
Large language models (LLMs) are widely deployed in various downstream tasks, e.g., auto-completion, aided writing, or chat-based text generation. However, the considered output ca…
SyntaxShap: Syntax-aware Explainability Method for Text Generation
Kenza Amara, Rita Sevastjanova, Mennatallah El-Assady
To harness the power of large language models in safety-critical domains, we need to ensure the explainability of their predictions. However, despite the significant attention to m…
PowerGraph: A power grid benchmark dataset for graph neural networks
Anna Varbella, Kenza Amara, Blazhe Gjorgiev +2
Power grids are critical infrastructures of paramount importance to modern society and, therefore, engineered to operate under diverse conditions and failures. The ongoing energy t…