Summary of Auditllm: a Tool For Auditing Large Language Models Using Multiprobe Approach, by Maryam Amirizaniani et al.
AuditLLM: A Tool for Auditing Large Language Models Using Multiprobe Approach
by Maryam Amirizaniani, Elias Martin, Tanya Roosta, Aman Chadha, Chirag Shah
First submitted to arxiv on: 14 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed “AuditLLM” tool is designed to audit the performance of Large Language Models (LLMs) by probing their knowledge base or functional capacity. The tool uses multiple probes derived from a single question to detect inconsistencies and generate semantically similar responses. It’s expected that robust LLMs will produce consistent results, while inconsistent models may indicate potential bias or hallucinations. AuditLLM offers two modes: live mode for instant auditing of LLMs and batch mode for comprehensive analysis. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The “AuditLLM” tool helps ensure the reliability and safety of Large Language Models (LLMs) by detecting inconsistencies in their performance. This is done by asking a single question and generating multiple probes to test the model’s understanding. The tool can identify potential bias or hallucinations, making it useful for both researchers and general users. |
Keywords
» Artificial intelligence » Knowledge base
