| cff-version: 1.2.0 | |
| message: "If you use TMCRA, please cite this software. OpenAI Codex assisted with development and reproducibility engineering." | |
| title: "TMCRA — Agent Memory Engine" | |
| type: software | |
| version: "2026.07.18" | |
| date-released: 2026-07-18 | |
| license: Apache-2.0 | |
| authors: | |
| - family-names: Yu | |
| given-names: Haoxin | |
| alias: reshuibuduo | |
| website: "https://github.com/reshuibuduo" | |
| - name: "OpenAI Codex" | |
| website: "https://openai.com/codex/" | |
| repository-code: "https://github.com/reshuibuduo/TMCRA-Agent-Memory" | |
| url: "https://github.com/reshuibuduo/TMCRA-Agent-Memory" | |
| abstract: >- | |
| TMCRA is an agent memory engine that builds scope-isolated, source-traceable | |
| memory from long-running conversations and compiles relevant evidence for | |
| downstream agents. This release includes the algorithm snapshot, learned | |
| graph-scoring artifacts, and a reproducible LongMemEval pipeline. | |
| keywords: | |
| - agent memory | |
| - long-term memory | |
| - memory graph | |
| - retrieval | |
| - LongMemEval | |