Publish AutoMemoryBench paper artifacts

.gitattributes

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+AutoMemoryBench-arXiv.pdf filter=lfs diff=lfs merge=lfs -text

AutoMemoryBench-arXiv-source.tar.gz

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AutoMemoryBench-arXiv.pdf

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README.md

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+---
+language:
+- en
+pretty_name: AutoMemoryBench
+tags:
+- benchmark
+- agent-memory
+- memory-systems
+- llm-agents
+- evaluation
+---
+
+# AutoMemoryBench
+
+**State-Contract Evaluation for Auditable Agent Memory**
+
+AutoMemoryBench evaluates whether an agent uses the right memory, and only the
+admissible memory, under a query-time state contract. Each contract partitions
+memory into required, admissible, and prohibited sets, with prohibited memories
+typed as superseded, deleted, restricted, cross-namespace, or stale-tool.
+
+## Paper
+
+- [Paper PDF](AutoMemoryBench-arXiv.pdf)
+- [arXiv source package](AutoMemoryBench-arXiv-source.tar.gz)
+- [Code and data](https://github.com/wuyuVerse/AutoMemoryBench)
+
+## Authors
+
+Jiajun Wu, Jian Yang, Chen Li, Linzheng Chai, Ge Gao, Ensheng Shi, and Yuchi Ma.
+
+Jiajun Wu and Jian Yang are affiliated with Beihang University. Ensheng Shi and
+Yuchi Ma are affiliated with Huawei Cloud Computing Technologies Co., Ltd.
+
+## Abstract
+
+A deployed agent fails not only when it forgets, but when it uses memory that is
+stale, deleted, unauthorized, cross-namespace, or unsupported by current tool
+state. AutoMemoryBench introduces query-time memory admissibility as an
+executable evaluation contract. Its primary metric, StrictCore, counts a query
+only when the task is solved, required evidence is used, and no prohibited
+memory influences the output. The release spans eight domains with 7,200 case
+variants and 151,200 probes, paired with minimal single-axis interventions.
+
+## Citation
+
+```bibtex
+@misc{automemorybench,
+  title  = {AutoMemoryBench: State-Contract Evaluation for Auditable Agent Memory},
+  author = {Wu, Jiajun and Yang, Jian and Li, Chen and Chai, Linzheng and
+            Gao, Ge and Shi, Ensheng and Ma, Yuchi},
+  year   = {2027},
+  url    = {https://github.com/wuyuVerse/AutoMemoryBench}
+}
+```
+
+The formal Hugging Face Paper page and arXiv link will be added after the paper
+receives an arXiv identifier.
+
+## License
+
+The code and benchmark data are released under Apache-2.0. The paper license
+will follow the license selected for the arXiv submission.

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+678613bfa33523e5b26eec4e85a12fc2ffc8d46059f572d271fbf0954a23902b  AutoMemoryBench-arXiv.pdf