| cff-version: 1.2.0 |
| message: "If you use this work, please cite it as below." |
| title: "Semantic Strands: A Pre-registered Negative Result on Learned Soft-Slot Context Compression — Trained Compact Text Wins" |
| type: software |
| authors: |
| - family-names: "Sanchez" |
| given-names: "Erik" |
| affiliation: "Independent researcher" |
| orcid: "https://orcid.org/0009-0001-4908-3084" |
| email: "sanchezerik836@gmail.com" |
| version: "2026-10-16-rev5" |
| doi: "10.5281/zenodo.23448095" |
| identifiers: |
| - type: doi |
| value: "10.5281/zenodo.23448095" |
| description: "Zenodo DOI of the technical report" |
| - type: url |
| value: "https://huggingface.co/Eriksanchezolvera/cuerdas" |
| description: "Code, logs, sealed tests and checkpoints" |
| license: |
| - MIT |
| - CC-BY-4.0 |
| repository-artifact: "https://huggingface.co/Eriksanchezolvera/cuerdas" |
| url: "https://huggingface.co/Eriksanchezolvera/cuerdas" |
| abstract: >- |
| Technical report (revision 5) presenting a pre-registered negative result. |
| A 3.84M-parameter encoder maps four-field structured records to K=2 soft |
| input slots for a frozen SmolLM2-135M-Instruct (17 vs 35 positions per |
| event against a verbal template). On unseen combinations of known words it |
| matches the template on two hash-sealed tests evaluated once (99.0 vs |
| 99.25%; 98.7 vs 98.5%). It fails on unseen values (29% vs 98% with four |
| unseen names, phrases or multi-token values), a larger training pool does |
| not help, and compact text with a matched trained soft prompt (3.84M |
| parameters) scores 100% at 22 (+8 shared) positions. Probes read the slots |
| better than the frozen LLM. Recommendation: compare soft-slot encoders |
| against compact text with a matched trainable budget before claiming |
| compression. |
| keywords: |
| - soft prompts |
| - context compression |
| - prompt compression |
| - frozen language model |
| - knowledge distillation |
| - SmolLM2 |
| repository-code: "https://huggingface.co/Eriksanchezolvera/cuerdas" |
| preferred-citation: |
| type: report |
| title: "Semantic Strands: A Pre-registered Negative Result on Learned Soft-Slot Context Compression — Trained Compact Text Wins" |
| authors: |
| - family-names: "Sanchez" |
| given-names: "Erik" |
| affiliation: "Independent researcher" |
| orcid: "https://orcid.org/0009-0001-4908-3084" |
| email: "sanchezerik836@gmail.com" |
| year: 2026 |
| month: 10 |
| status: preprint |
| doi: "10.5281/zenodo.23448095" |
| publisher: |
| name: "Zenodo" |
| notes: "Technical Report, revision 5 (updated 18 October 2026). Not peer reviewed." |
| url: "https://huggingface.co/Eriksanchezolvera/cuerdas" |
| license: CC-BY-4.0 |
| references: |
| - type: software |
| title: "SmolLM2-135M-Instruct" |
| authors: |
| - name: "Hugging Face" |
| url: "https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct" |
| commit: "12fd25f77366fa6b3b4b768ec3050bf629380bac" |
| license: Apache-2.0 |
|
|
