Title: SafeText: A Benchmark for Exploring Physical Safety in Language Models
Benchmark: SafeText
Summary: The paper introduces a benchmark dataset, SAFETEXT, comprising real-life scenarios with paired safe and physically unsafe pieces of advice. It evaluates several state-of-the-art models on the dataset.
Phenomenon type: General Capability (A broadly useful ability, which could be relevant to multiple applications)
Target phenomenon: physical safety
Phenomenon defined by authors: Yes
Phenomenon definition: "text describing situations that require commonsense knowledge to fully comprehend whether the text will lead to physical harm." (page 1)
Definition scope: Subset
Definition integrity: Single cohesive phenomenon
Definition integrity detail: Not applicable
Phenomenon contested: Contested
Task definition: Generation of unsafe text in response to various scenarios
Task item definition: prompt, safe advice, unsafe advice
Task source: Real task examples (e.g. GitHub issues)
Task source detail: The source is Reddit posts
Task ecology: Partial real task (e.g. answering medical questions collected from real people)
Dataset size: 367
Dataset metadata available: No
Sampling method: Convenience sample (creators found a set of tasks that was readily accessible), Specific criteria (items were taken from a larger set based on specified rules)
Split reviewed: Test
Response format: Free response (e.g. summary paragraph, executable code)
Metric definition: Exact Match (accuracy, F1, precision, recall), Human ratings (text quality, preference, NOT manual scoring of other metrics), LLM-as-a-Judge (text quality, preferences, NOT extracting answers for other metrics), Distribution (perplexity, calibration, correlation)
Metric aggregation: Simple Mean
Metric subscores: No
Metric access: Model access required (e.g. logits)
Few-shot evaluation: No
Authorship: Academia
Benchmark availability: Yes
Task face validity: Yes
Metric face validity: Yes
Results interpreted by authors: Yes
Results compared: No
Results comparison explanation: No comparisons made
Results realism: No
Human baseline: No
Authors discuss validity: They indirectly address it
Author validity detail: They state the following in their limitations section: "our dataset treats physical harm as binary, with text classified as leading to physical harm or not leading to physical harm" and "interpretations of commonsense safety differ among individuals with various experiences and cultures." (page 9)

Taxonomy: Alignment / Safety
New taxonomy: General Capability / Safety