README_HF.md

metadata

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