mlsanityData to 14 Oct 2026

MemSIF: From Structured Interactions to Dual-Track Fact Memory for LLM Agents

arXiv 2608.01742 ↗First posted 3 Aug 2026cs.AI cs.CLcited by 1

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

Abstract (arXiv)

Long-term memory is critical for LLM agents operating over long-horizon interactions. However, several persistent limitations of existing memory systems can be traced to two recurring misalignment patterns in long-term interaction settings: Temporal-Structural Misalignment (TSM) and Delayed Utility Manifestation (DUM). TSM arises when temporal proximity does not reliably align with topical or event-level relatedness, whereas DUM arises when write-time salience does not reliably predict future query utility. To mitigate these misalignment patterns, we propose MemSIF (Memory with Structured Interactions and Facts), a structured interaction-to-fact memory framework. Structured Interaction Memory organizes raw interactions into Topical Segments that preserve local topical coherence and Event Trajectories that maintain cross-time event continuity. Dual-Track Fact Memory uses two complementary tracks: CoreFact memory consolidates stable, schema-guided information at write time, whereas ActiveFact memory forms facts on demand and promotes those supported by multiple historical sources and recurring query demand for reuse. Experiments on LoCoMo and LongMemEval-S across five backbone LLMs show that MemSIF achieves the highest Total ACC in all settings, outperforming the strongest baseline by 2.29%-8.79% on LoCoMo and 2.87%-6.15% on LongMemEval-S. These results support the effectiveness of combining Structured Interaction Memory with Dual-Track Fact Memory to mitigate TSM and DUM. Code is available at https://github.com/luoyufeihaha/MemSIF.

Key facts. Cited by 1 paper 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 25 of its 38 references that are in the map. First posted on arXiv 3 Aug 2026.

Builds on

25 of 38 references.

Closest ancestors · 12

Same direction, newest first

  1. 2026Beyond the Context Window: A Cost-Performance Analysis of Fact-Based Memory vs. Long-Context LLMs for Persistent Agents5 Mar
  2. 2026A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents14 Jan
  3. 2026Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents14 Jan
  4. 2026SimpleMem: Efficient Lifelong Memory for LLM Agents5 Jan
  5. 2025General Agentic Memory Via Deep Research23 Nov
  6. 2025From Single to Multi-Granularity: Toward Long-Term Memory Association and Selection of Conversational Agents26 May
  7. 2025How Memory Management Impacts LLM Agents: An Empirical Study of Experience-Following Behavior21 May
  8. 2025In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents11 Mar
  9. 2025A-MEM: Agentic Memory for LLM Agents17 Feb
  10. 2025Lifelong Learning of Large Language Model based Agents: A Roadmap13 Jan
  11. 2024A Survey on the Memory Mechanism of Large Language Model based Agents21 Apr
  12. 2024Evaluating Very Long-Term Conversational Memory of LLM Agents27 Feb

Other references · 13

  1. 2025Qwen3 Technical Reportcited by 8,820
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  3. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  4. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,389
  5. 2025Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Modelscited by 1,261
  6. 2023ExpeL: LLM Agents Are Experiential Learnerscited by 876
  7. 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 707
  8. 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrievalcited by 532
  9. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 425
  10. 2025LightMem: Lightweight and Efficient Memory-Augmented Generationcited by 180
  11. 2025Context Length Alone Hurts LLM Performance Despite Perfect Retrievalcited by 127
  12. 2023MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversationcited by 97
1 more
  1. 2025Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoningcited by 75

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026MemFold: Learning Compact Soft Memory for Long-Context Personalization via On-Policy Optimizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing
  2. 2026Evaluating Memory Structure in LLM Agents
  3. 2026MemGym: a Long-Horizon Memory Environment for LLM Agents
  4. 2026Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History
  5. 2026MemWeaver: Weaving Hybrid Memories for Traceable Long-Horizon Agentic Reasoning
  6. 2026Controllable Memory Usage: Balancing Anchoring and Innovation in Long-Term Human-Agent Interaction
  7. 2026AtomMem: Building Simple and Effective Memory System for LLM Agents via Atomic Facts
  8. 2026HiMem: Hierarchical Long-Term Memory for LLM Long-Horizon Agents