Datasets:
Tasks:
Other
Formats:
json
Languages:
English
Size:
< 1K
Tags:
research-paper
agent-memory
temporal-memory
entity-aware-retrieval
privacy
evaluation-protocol
License:
| pretty_name: KLIK Temporal Memory Paper | |
| license: cc-by-4.0 | |
| task_categories: | |
| - other | |
| language: | |
| - en | |
| tags: | |
| - research-paper | |
| - agent-memory | |
| - temporal-memory | |
| - entity-aware-retrieval | |
| - privacy | |
| - evaluation-protocol | |
| size_categories: | |
| - n<1K | |
| configs: | |
| - config_name: publication-record | |
| data_files: | |
| - split: train | |
| path: paper.jsonl | |
| # KLIK Temporal Memory Paper | |
| This dataset is the public research record for **KLIK Temporal, Entity-Aware, Privacy-Constrained Memory**. It packages the public-edition manuscript, a citation record, and a machine-readable publication entry. | |
| ## What this release is | |
| - A scoped architecture proposal for temporal, entity-aware, privacy-constrained agent memory. | |
| - A preregistered protocol for comparing the proposed system with registered controls and memory baselines. | |
| - An evidence-readiness audit that keeps historical retrieval observations separate from unmeasured target-architecture results. | |
| ## What this release is not | |
| - Not a claim that the proposed architecture has already beaten all memory systems. | |
| - Not a release of private product data, customer data, source checkouts, private repository paths, or internal commit identifiers. | |
| - Not an empirical benchmark dataset or a substitute for the frozen-run artifacts required by the paper. | |
| ## Files | |
| | Path | Description | | |
| | --- | --- | | |
| | `klik-temporal-memory-evaluation-paper.public.en.md` | Public-edition manuscript source. | | |
| | `klik-temporal-memory-evaluation-paper.public.en.pdf` | Public-edition rendered paper. | | |
| | `paper.jsonl` | Machine-readable publication metadata. | | |
| | `CITATION.cff` | Citation metadata. | | |
| ## Claim boundary | |
| The paper defines a bounded superiority criterion: any future claim must be limited to registered datasets, comparator versions, runtime conditions, and preregistered statistical and safety gates. It deliberately does not invent an unobserved result. | |