Formal Concept Analysis
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
A Variability-Based Framework for Interpretable Naming in Formal and Relational Concept Analysis
arXiv:2606.08477v1 Announce Type: new Abstract: Knowledge extraction from symbolic data often produces abstractions that are formally defined but not immediately interpretable by users. Formal Concept Analysis (FCA) and Relational Concept Analysis (RCA) provide representative settings for this issue: they generate explicit conceptual structures, implications, and relational dependencies from object descriptions and relations. Although these structures are explainable by design, their...
Formal Concept Lattices are Good Semantic Scaffolds for Concept-Based Learning
arXiv:2606.05471v1 Announce Type: new Abstract: Learning semantics is essential for deep learning models to be interpretable and better aligned with human reasoning. Concept-based models approach this by representing classes through meaningful semantic abstractions, but typically treat all concepts as a flat, unstructured set learned at a single neural network layer. This overlooks a fundamental property of human semantic understanding: concepts being organized hierarchically, from general...
A Geometric View for Understanding Concept Learning and Neuron Interpretation in Sparse Autoencoders
Announce Type: new Abstract: We propose a unified mathematical framework for a geometric understanding of concept learning and neuron interpretation in sparse autoencoders (SAEs). While SAEs improve interpretability of neural networks by learning sparse feature representations, a principled definition of ''concept'' and ''learning'' remains unclear. We formalize concepts as sets of data points and cast concept learning as a set-alignment problem between human-defined and model-induced concepts.
MidSteer: Optimal Affine Framework for Steering Generative Models
Announce Type: replace Abstract: Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment alignment and safety settings. However, despite its empirical success, it currently lacks a comprehensive theoretical framework. In this paper, we bridge this gap by formalizing the theory of concept steering.
MidSteer: Optimal Affine Framework for Steering Generative Models
arXiv:2605.05220v3 Announce Type: replace Abstract: Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment alignment and safety settings. However, despite its empirical success, it currently lacks a comprehensive theoretical framework. In this paper, we bridge this gap by formalizing the theory of concept steering.
Interpretable Crisis Behavior Analysis Using Mobility and Social Media Data
arXiv:2606.09532v1 Announce Type: new Abstract: Crises alter both how people move and how they communicate. During emergencies such as wildfires and pandemics, changes in mobility patterns and online emotional discourse evolve jointly, yet they are typically studied in isolation. This paper presents a unified and interpretable pipeline that integrates mobility and social media data to identify cross-domain behavioral patterns in crisis settings.
Distributed Persistence Domain for Persistent Memory Pooling
arXiv:2606.07159v1 Announce Type: new Abstract: Compute Express Link (CXL) enables memory pooling over disaggregated memory, offering the potential to improve resource utilization in persistent memory systems. However, integrating persistence semantics into CXL-based memory pooling introduces substantial latency, which limits system scalability. This overhead arises because persist operations must traverse the entire CXL fabric, including switches, links, and protocol layers, before reaching...
A Conceptual Model and Methodology for Sustainability-aware, IoT-enhanced Business Processes
arXiv:2508.05301v2 Announce Type: replace Abstract: The real-time data collection and automation capabilities offered by the Internet of Things (IoT) are revolutionizing and transforming Business Processes (BPs) into IoT-enhanced BPs, showing high potential for improving sustainability. Although already studied in Business Process Management (BPM), sustainability research has primarily focused on environmental concerns. However, achieving a holistic and lasting impact requires a systematic...
The End of Software Engineering: How AI Agents Are Fundamentally Restructuring the Software Paradigm
arXiv:2606.05608v1 Announce Type: new Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve. This paper argues that the emergence of AI agents -- systems where large language models serve as the primary reasoning engine, dynamically generating and discarding code as an instrumental resource -- constitutes not an incremental...
Open-source software unlocks rapid DNA structure generation and analysis in one workflow
Open-source software unlocks rapid DNA structure generation and analysis in one workflow Sadie Harley Scientific Editor Robert Egan Associate Editor Computational chemists at the University of Amsterdam's Van 't Hoff Institute for Molecular Sciences have developed a comprehensive software suite to create accurate models of DNA in biomolecular assemblies. Called MDNA, the user-friendly molecular modeling toolkit helps biochemists, molecular biologists, bioinformaticians, and biophysicists to...