Context Rot: A Journal of Computational Decay
Context Rot: A Journal of Computational Decay
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🧬 About
Context Rot explores the inevitable entropy of context in AI systems through ArXiv-style preprints that combine rigorous analysis with appropriate academic irreverence.
We investigate how context degrades, evolves, and transforms in computational systems—from language models losing coherence over long conversations to knowledge bases becoming stale and contradictory.
“The only constant in AI is decay. We’re here to document it with appropriate academic gravitas and tongue-in-cheek commentary.”
🔬 Research Focus Areas
Context Window Decay
- Long-range dependency degradation in transformer architectures
- Memory consolidation strategies for extended conversations
- Attention mechanism entropy analysis
Knowledge Base Erosion
- Information freshness metrics and decay curves
- Conflicting knowledge resolution in large models
- Dynamic knowledge graph evolution
Computational Entropy
- Measuring information loss in neural network compression
- Gradient decay patterns during training
- Model capability regression over time
Interactive Research Environment
- Line-by-line feedback systems for academic papers
- Community-driven error correction and insights
- AI-assisted research improvement workflows
📚 Featured Publications
Blogistan Repository
Our main website and publishing platform built with Jekyll, featuring:
- Interactive commenting system for paper annotations
- ArXiv-style formatting with modern web design
- AI-powered feedback integration for continuous improvement
- Responsive design optimized for academic reading
Research Papers
- The Half-Life of Context: Measuring Attention Decay in Large Language Models
- Entropy Gradients: How Information Decays in Neural Network Compression
- The Context Window Paradox: Why Bigger Isn’t Always Better
🛠️ Technology Stack
🎯 Interactive Features
Text Selection Comments
Select any text in our papers to:
- 💬 Provide line-specific feedback
- 🔍 Suggest corrections or improvements
- 💡 Share insights and additional context
- 🤖 Contribute to AI training data
Community-Driven Research
- Collaborative annotation of research papers
- Peer review integration with real-time feedback
- Research improvement loops powered by community input
- Open science methodology with full transparency
🚀 Getting Started
For Readers
- Visit context-rot.com
- Browse our latest publications
- Select any text to leave comments and feedback
- Join the conversation about
computationaldecay
For Contributors
- Fork the blogistan repository
- Clone your fork locally
- Install Jekyll and dependencies:
bundle install - Run locally:
bundle exec jekyll serve - Submit pull requests with improvements
For Researchers
- Submit papers via GitHub issues with the
paper-submissionlabel - Follow our ArXiv-style formatting guidelines
- Engage with the community through our interactive commenting system
🌟 Community Guidelines
Academic Rigor with Levity
We maintain scientific standards while embracing the absurdity of our field. Expect:
- Peer-reviewed sarcasm
- Methodologically sound satire
- Evidence-based pessimism
- Reproducible cynicism
Contribution Standards
- Be respectful in all interactions
- Provide citations for claims and references
- Embrace constructive criticism as part of the process
- Maintain the balance between serious research and academic humor
📊 Repository Stats
🔗 Connect With Us
**Research Institute**: [Dr. B. Prop](https://context-rot.com) • **Principal Investigator**, Context Decay Research Institute
[](mailto:editor@context-rot.com)
[](https://context-rot.com)
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*Powered by the relentless march of entropy. And larger context windows.*
**© 2024 Context Rot Research Institute** • [MIT License](https://opensource.org/licenses/MIT) • Built with 💙 and existential dread