Search Results for author:
Found 12 papers, 1 papers with code
P-DBSCAN: A density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos
The rapid spread of location-based devices and cheap storage mechanisms, as well as fast development of Internet technology, allowed collection and distribution of huge amounts of user-generated data, such as people’s movement or geo-tagged photos.
Visual Integration of Data and Model Space in Ensemble Learning
Ensembles of classifier models typically deliver superior performance and can outperform single classifier models given a dataset and classification task at hand.
lingvis.io - A Linguistic Visual Analytics Framework
We present a modular framework for the rapid-prototyping of linguistic, web-based, visual analytics applications.
Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections
We present a framework that allows users to incorporate the semantics of their domain knowledge for topic model refinement while remaining model-agnostic.
Should We Trust (X)AI? Design Dimensions for Structured Experimental Evaluations
This paper systematically derives design dimensions for the structured evaluation of explainable artificial intelligence (XAI) approaches.
A Comparative Analysis of Industry Human-AI Interaction Guidelines
We have then used this framework to compare each of the surveyed companies to find differences in areas of emphasis.
Human-Computer Interaction
The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inference
We motivate the use of visualization in relation to target users and common NLP pipelines.
RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback
To use reinforcement learning from human feedback (RLHF) in practical applications, it is crucial to learn reward models from diverse sources of human feedback and to consider human factors involved in providing feedback of different types.
Is that really a question? Going beyond factoid questions in NLP
Research in NLP has mainly focused on factoid questions, with the goal of finding quick and reliable ways of matching a query to an answer.
