Datasets:
| pretty_name: FalseMemBench | |
| license: mit | |
| task_categories: | |
| - text-retrieval | |
| language: | |
| - en | |
| tags: | |
| - retrieval | |
| - memory | |
| - llm-agents | |
| - adversarial | |
| size_categories: | |
| - n<1K | |
| # FalseMemBench | |
| This dataset contains adversarial distractor cases for evaluating memory retrieval systems used by LLM agents. | |
| Each case contains: | |
| - a query | |
| - a small candidate corpus | |
| - one or more relevant entry ids | |
| - an adversary type label | |
| The dataset is intended for evaluating retrieval under confusion pressure rather than open-ended generation. | |
| Current adversary types: | |
| - entity swap | |
| - environment swap | |
| - time swap | |
| - state update | |
| - speaker swap | |
| - near-duplicate paraphrase | |
| Current dataset size: | |
| - `573` cases | |