This archive presents five working papers on context compression failure modes in large language models. The central finding is the validity mirage: naive context compression can preserve surface-level answer correctness while silently substituting the governing hypothesis, causing a model to answer confidently about the wrong task. We develop a tropical semiring algebra (max-plus over ℝ ∪ −∞) for measuring context health under compression, and show that structurally guarded retention policies eliminate pivot drift where recency-based baselines fail completely. Empirical validation spans five open-weight model architectures (Llama 3. 1 8B, Mistral 7B v0. 3, Gemma 2 9B, Phi-3 Medium 14B, Qwen 2. 5 14B) across 11, 400+ boundary instances and 4, 200+ streaming trials, with additional testing against 13 real incident graphs (12 NTSB aviation investigations and the Knight Capital 2012 trading failure). A production MCP server implementation is available separately. Included papers: Paper 00: Continuous Control and Structural Regularization in Multi-Agent Narrative ExtractionPaper 01: Absorbing States in Greedy SearchPaper 02: Streaming Oscillation Traps in Endogenous-Pivot Sequential ExtractionPaper 03: The Validity Mirage: Context Algebra for Endogenous Semantics under Memory CompressionPaper I: Tropical Algebra of Endogenous-Pivot Semantics Reproducible validation artifacts and benchmark outputs are included in the results/ directory. All papers are working paper first drafts distributed under CC-BY 4. 0.
Jack Chaudier Gaffney (Mon,) studied this question.