mlsanityData to 14 Oct 2026

Text2Mem: A Unified Memory Operation Language for Memory Operating System

arXiv 2509.11145 ↗First posted 14 Sep 2025cs.CL cs.PLcited by 3

On the map: LLM agents and tool use → Agent memory systems

Abstract (arXiv)

Large language model agents increasingly depend on memory to sustain long horizon interaction, but existing frameworks remain limited. Most expose only a few basic primitives such as encode, retrieve, and delete, while higher order operations like merge, promote, demote, split, lock, and expire are missing or inconsistently supported. Moreover, there is no formal and executable specification for memory commands, leaving scope and lifecycle rules implicit and causing unpredictable behavior across systems. We introduce Text2Mem, a unified memory operation language that provides a standardized pathway from natural language to reliable execution. Text2Mem defines a compact yet expressive operation set aligned with encoding, storage, and retrieval. Each instruction is represented as a JSON based schema instance with required fields and semantic invariants, which a parser transforms into typed operation objects with normalized parameters. A validator ensures correctness before execution, while adapters map typed objects either to a SQL prototype backend or to real memory frameworks. Model based services such as embeddings or summarization are integrated when required. All results are returned through a unified execution contract. This design ensures safety, determinism, and portability across heterogeneous backends. We also outline Text2Mem Bench, a planned benchmark that separates schema generation from backend execution to enable systematic evaluation. Together, these components establish the first standardized foundation for memory control in agents.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 23 of its 24 references that are in the map. First posted on arXiv 14 Sep 2025.

Builds on

23 of 24 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory28 Apr
  2. 2025A-MEM: Agentic Memory for LLM Agents17 Feb
  3. 2025Zep: A Temporal Knowledge Graph Architecture for Agent Memory20 Jan

Other references · 20

  1. 2023A Survey of Large Language Modelscited by 2,576
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  3. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,389
  4. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
  5. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 688
  6. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 687
  7. 2023MemoryBank: Enhancing Large Language Models with Long-Term Memorycited by 556
  8. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 424
  9. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 281
  10. 2025From RAG to Memory: Non-Parametric Continual Learning for Large Language Modelscited by 231
  11. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 205
  12. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 185
8 more
  1. 2024A Comprehensive Study of Knowledge Editing for Large Language Modelscited by 163
  2. 2025MemOS: A Memory OS for AI Systemcited by 138
  3. 2024Memory3: Language Modeling with Explicit Memorycited by 40
  4. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  5. 2025AI-native Memory 2.0: Second Mecited by 14
  6. 2024Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learningcited by 13
  7. 2025EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language Modelscited by 7
  8. 2025LogicCat: A Chain-of-Thought Text-to-SQL Benchmark for Complex Reasoningcited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025MemOS: An Operating System for Memory-Augmented Generation (MAG) in Large Language Models
  2. 2026UMEM: Unified Memory Extraction and Management Framework for Generalizable Memory
  3. 2026AgentSM: Semantic Memory for Agentic Text-to-SQL
  4. 2025MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents
  5. 2026Memory Architectures for Multi-Turn Text-to-SQL: A Benchmark and Empirical Study
  6. 2026Are We Ready For An Agent-Native Memory System?
  7. 2026PLACEMEM: Toward a Compute-Aware Memory Plane for Lifelong Agents
  8. 2026Memory as Infrastructure: Reliability Engineering for Persistent Agent Memory in Months-Long LLM-Assisted Development