---
title: "StructMem: Structured Memory for Long-Horizon Behavior in LLMs"
description: "StructMem proposes a middle path built on a different memory unit: the temporally anchored relational event. 31 references."
authors: ["Buqiang Xu", "Yijun Chen", "Jizhan Fang", "Ruobin Zhong", "Yunzhi Yao", "Yuqi Zhu", "Lun Du", "Shumin Deng"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)"
source: "https://aclanthology.org/2026.acl-short.12/"
doi: "10.18653/v1/2026.acl-short.12"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/xu-2026-structmem-structured-memory-long-horizon/"
---
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# StructMem: Structured Memory for Long-Horizon Behavior in LLMs

**Authors:** Buqiang Xu, Yijun Chen, [Jizhan Fang](https://md.research.elamur.ai/free/en/authors/jizhan-fang/), Ruobin Zhong, [Yunzhi Yao](https://md.research.elamur.ai/free/en/authors/yunzhi-yao/), [Yuqi Zhu](https://md.research.elamur.ai/free/en/authors/yuqi-zhu/), [Lun Du](https://md.research.elamur.ai/free/en/authors/lun-du/) and [Shumin Deng](https://md.research.elamur.ai/free/en/authors/shumin-deng/) · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.acl-short.12/) · [PDF](https://aclanthology.org/2026.acl-short.12.pdf) · [DOI 10.18653/v1/2026.acl-short.12](https://doi.org/10.18653/v1/2026.acl-short.12) · [OpenAlex](https://openalex.org/W7166823995)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Conversational agents that run for a long time need memory that tracks how events connect, not just isolated facts. Flat memory stores are cheap but lose cross-event links. Graph memories recover structure through entity and relation extraction, but they are costly and prone to compounding extraction errors. StructMem proposes a middle path built on a different memory unit: the temporally anchored relational event.

For each utterance, an LLM writes two kinds of natural-language entries, one factual and one relational (interpersonal, causal, temporal). Both share the utterance's timestamp, so full events can be rebuilt at retrieval time. New entries are also buffered. Periodically, the buffer is embedded as a single query that pulls semantically similar past events, and an LLM synthesizes cross-event relational hypotheses from them.

On LoCoMo, StructMem gets the highest overall LLM-judge score among the compared systems. It also needs far fewer tokens, API calls, and seconds of runtime for memory construction. This suggests structured reasoning over memory does not require maintaining a full graph.

## Key points
- On LoCoMo, StructMem scores 76.82 overall, ahead of Memobase (75.78), Zep (75.14), and FullContext (73.83). It is best on single-session questions (81.09) and second on temporal ones (81.62, behind Memobase's 85.05). On multi-hop it reaches 68.77, below Zep (74.11) and Memobase (70.92).
- Construction cost compared with Mem0 g:
  - Tokens: ~1.94M vs ~35.8M.
  - API calls: 1,056 vs 53,514.
  - Runtime: ~22.9k s vs ~115.7k s.
- In the ablation, removing cross-event consolidation lowers multi-hop from 68.77 to 66.31 and temporal from 81.62 to 79.44.
- Simply retrieving more entries stops helping: flat retrieval plateaus at about 60 entries. Adding semantic seeds lifts the score from 75.71 with no seeds (K=0) to a peak of 76.82.
- The authors acknowledge two limitations: results depend heavily on the extraction prompts, and the system has no mechanism for memory updating or resolving conflicting facts. Code is released in the zjunlp/LightMem repository.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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- [Ant Group](https://md.research.elamur.ai/free/en/companies/ant-group/) — Company, Hangzhou, China · 51 works · 1,211 citations

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## Cite

Cite as: Buqiang Xu, Yijun Chen, Jizhan Fang, Ruobin Zhong, Yunzhi Yao, Yuqi Zhu, Lun Du and Shumin Deng. 2026. StructMem: Structured Memory for Long-Horizon Behavior in LLMs. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{xu2026structmem,
  title = {{StructMem: Structured Memory for Long-Horizon Behavior in LLMs}},
  author = {Buqiang Xu, Yijun Chen, Jizhan Fang, Ruobin Zhong, Yunzhi Yao, Yuqi Zhu, Lun Du and Shumin Deng},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-short.12},
  url = {https://doi.org/10.18653/v1/2026.acl-short.12}
}
```

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*Updated 2 November 2026*