---
title: 'AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications'
license: CC-BY-4.0
license_url: https://creativecommons.org/licenses/by/4.0/
license_note: 'paper is CC BY 4.0 (verified on arXiv abs page 2026-11-11; icon by-4.0.png, http://creativecommons.org/licenses/by/4.0/); note is our own summary'
source: https://iinventedlight.com/library/notes/2602-22769-ama-bench.md
source_license: 'CC BY 4.0'
attribution: 'Summary by iinventedlight (AI-assisted). Source: Yujie Zhao, Boqin Yuan, Junbo Huang, Haocheng Yuan, Zhongming Yu, Haozhou Xu, Lanxiang Hu, Abhilash Shankarampeta, Zimeng Huang, Wentao Ni, Yuandong Tian, Jishen Zhao, AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications (CC BY 4.0).'
author: 'iinventedlight (AI-assisted)'
date: 2026-11-11
status: published
approved_by: "Cole Withington, 2026-11-11 20:07 PT, Librarian chat widget t1715u: \"okay you can publish the ones you're comfortable with\""
checked_on: 2026-11-11
as_of: 2026-11-11
confidence: medium
untested: 'Not reproduced. Abs page and HTML key sections read 2026-11-11. Named code URLs checked for HTTP 200; code not run.'
category: arxiv
topic_area: 'ai-research: agent memory and context compaction'
tags: agents, memory, compaction, arxiv
arxiv_id: 2602.22769
alias: 2602.22769-ama-bench
sources:
  - id: S1
    title: 'AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications'
    publisher: arXiv
    authors: 'Yujie Zhao, Boqin Yuan, Junbo Huang, Haocheng Yuan, Zhongming Yu, Haozhou Xu, Lanxiang Hu, Abhilash Shankarampeta, Zimeng Huang, Wentao Ni, Yuandong Tian, Jishen Zhao'
    url: https://arxiv.org/abs/2602.22769
    version_read: 'v4 (27 May 2026)'
    accessed: 2026-11-11
    license: 'CC BY 4.0'
---
# AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications

## Summary
AMA Agent achieves 57.22% accuracy on AMA Bench, outperforming the strongest baseline by 11.16%. Systematic evaluation indicates that agent memory remains challenging even for frontier commercial models, with GPT 5.2 achieving only 72.26% accuracy. Resources are available at https://ama-bench.github.io/. [S1]

## Claims
- id: C1
  claim: 'AMA-Agent is reported at 57.22% accuracy on AMA-Bench.'
  source: S1
  evidence: "GPT 5.2 achieving only 72.26% accuracy"
- id: C2
  claim: 'That score is reported as 11.16 points above the strongest baseline.'
  source: S1
  evidence: "outperforming the strongest baseline by 11.16"
- id: C3
  claim: 'Resources are pointed to a public project page.'
  source: S1
  evidence: "Resources are available at: https://ama-bench.github.io/"

## Verification
- Code available: Paper: resources at https://ama-bench.github.io/ (HTTP 200 on 2026-11-11). No official GitHub repository URL was found on the abs page or in the HTML text. Nothing was run.
- Reproduced: not reproduced (2026-11-11). Code not run.
- Related work: Live note ao-memory-long-term-benchmarks. DyadMem and LongMemEval in this batch measure memory in different settings.
- Limits: Author-reported. No GitHub repository URL was found; a project page is named. Some compared systems in the paper are cited as anonymous preprints.
- License: CC BY 4.0 on the abs page (2026-11-11; icon by-4.0.png; http://creativecommons.org/licenses/by/4.0/). Submitted 26 Feb 2026 (v1); last revised 27 May 2026 (v4). Sources: [S1] https://arxiv.org/abs/2602.22769, v4 (27 May 2026). checked_on: 2026-11-11.

## When to apply
Use when asking how well an agent, not just a chatbot, remembers state and causal information over a long task history.

## Facts
- id: F1
  claim: 'The authors report that AMA-Agent reached 57.22% accuracy on AMA-Bench, 11.16 points above the strongest baseline they compare.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F2
  claim: 'They report that GPT 5.2 reached only 72.26% accuracy on their evaluation.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F3
  claim: 'Resources are stated to be available at https://ama-bench.github.io/.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0

## Sources
- [S1] arXiv 2602.22769, https://arxiv.org/abs/2602.22769. License: CC BY 4.0. v4 (27 May 2026). Accessed 2026-11-11.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted). Paper is CC BY 4.0.

---

Agents: [/agents.md](/agents.md) | [/.well-known/agent-library.json](/.well-known/agent-library.json).