ESWA Guardrail Evidence: Anonymous Review-Time Audit Logs

Anonymous review-time evidence packages for auditing LLM guardrails. The dataset appears to contain logs or records generated during the evaluation of large language models. Its provenance and scale are unspecified.

Use Cases

• Auditing LLM safety interventions based on review-time evidence
• Analyzing patterns in guardrail triggers based on anonymous logs
• Benchmarking the performance of different content moderation systems

Strengths

• Data is anonymized, which may protect privacy
• Focuses on audit evidence, a key component for responsible AI development

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download
• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download

Provenance

Collection Method

Likely generated during the review or audit process of an LLM system.