Semantic Infrastructure Lab - Research Publications
This directory contains formal research papers, technical deep-dives, and rigorous investigations conducted by the Semantic Infrastructure Lab. These papers represent SIL's commitment to treating semantic infrastructure as serious, foundational computer science—not prompt engineering or heuristics.
Philosophy
SIL approaches semantic infrastructure with the same rigor that operating systems, databases, and compilers receive:
- Formal problem analysis
- Geometric and algebraic foundations
- Measurable distortion/error metrics
- Provenance and reproducibility
- Engineering guidance derived from theory
These papers are working research documents—they evolve as we implement, test, and refine the ideas. Publication-ready versions will be prepared for peer review and archival venues.
Current Papers
RAG as Semantic Manifold Transport
Authors: Scott Senkeresty (Chief Architect, Semantic OS), Tia (Chief Semantic Agent)
Date: 2025-11-30
Status: Research Framework
Length: ~15,000 words
Abstract: Retrieval-Augmented Generation is not a retrieval problem—it is a semantic manifold transport problem. This paper formalizes RAG as meaning preservation across four geometrically misaligned representation spaces (human concepts, embeddings, LLM latents, fusion states), identifies distortion sources at each transition, and proposes rigorous alignment strategies.
Key Contributions:
- Geometric formalization of RAG as manifold transport
- Distortion analysis for each M_H → M_E → M_L → M_F transition
- Alignment strategies: scaffolding, reranking, structured fusion, provenance
- Connection to SIL architecture (Semantic Memory, USIR, Multi-Agent Orchestration)
- Implementation roadmap for low-distortion RAG
Why this matters: Most RAG systems fail due to geometric distortion, not retrieval quality. This framework provides engineering guidance for building semantically grounded, inspectable RAG.
Related SIL components: Layer 0 (Semantic Memory), Layer 1 (USIR), Layer 3 (Multi-Agent), Layer 5 (SIM)
Future Papers (Planned)
Universal Semantic Intermediate Representation (USIR)
Formal specification of the type system, composition operators, and cross-domain invariants for Layer 1 (Pantheon).
Provenance Manifolds in Multi-Agent Systems
How to track semantic transformations across agent boundaries while preserving causality and reproducibility.
Deterministic Scheduling in Cross-Domain Computation
Multirate scheduling, dependency resolution, and reproducibility guarantees in morphogen-style engines.
The Semantic Memory Problem
Requirements for persistent, provenance-complete semantic graphs that support geometric queries and relational reasoning.
Microkernel Architecture for Semantic Queries
Formal verification of query kernels (Prism-style) with property-based correctness proofs.
How to Read These Papers
For SIL Team Members
These papers provide:
- Formal foundations for implementation decisions
- Distortion/error metrics to optimize against
- Connection points between SIL layers
- Open research questions
Read them when designing new components or debugging semantic failures.
For Researchers
These papers are:
- Working documents (evolving as we implement)
- Accessible to systems/PL/ML researchers
- Grounded in real engineering constraints
- Open for collaboration and feedback
Treat them as research sketches, not finished publications.
For Engineers Building on SIL
These papers explain:
- Why SIL is architected this way
- What distortions/failures we're preventing
- How to extend SIL components rigorously
Focus on Section 4 (Strategies) and Section 5 (Connection to SIL Architecture) for implementation guidance.
Publication Status
Current status: Internal research documents
Future plans: Prepare for peer review and publication at:
- Academic venues (ICML, NeurIPS, PLDI, OSDI)
- arXiv preprints
- Industry conferences (Strange Loop, Papers We Love)
Contributing
Research contributions follow SIL's principles:
- Rigor first - Formal problem analysis, not hand-waving
- Provenance - Show derivations, cite inspirations
- Reproducibility - Provide metrics, benchmarks, code
- Clarity - Accessible to systems researchers, not just specialists
- Connection to architecture - How does this inform SIL design?
See main SIL repository for contribution guidelines.
Contact
For questions, collaborations, or feedback on these papers:
- GitHub Issues: Preferred for technical discussion
- Email: (contact information to be added)
Last Updated: 2025-11-30
License: CC BY 4.0 (documentation); to be determined for formal publications