TriEval: A Resource-Efficient Pipeline for LLM Bias, Toxicity, and Truthfulness Assessment
Quick Take
TriEval is an open-source pipeline for assessing LLMs like Llama 3, Mistral, and Claude Haiku on bias, toxicity, and truthfulness, requiring minimal computational resources. It effectively differentiates between open-source and closed-source models, revealing significant disparities in toxicity and truthfulness, making it accessible for researchers with limited resources.
Key Points
- TriEval evaluates LLM outputs on bias, toxicity, and truthfulness simultaneously.
- Compatible with open- and closed-source models, running on standard laptops.
- Tested on Llama 3 8B, Mistral 7B, Gemma 2 9B, and Claude Haiku.
- Significant differences found in toxicity and truthfulness between model types.
- Released as open source to support researchers with limited computational resources.
Article Content
From source RSS / original summaryarXiv:2606. 03036v1 Announce Type: new Abstract: LLMs have evolved from basic chatbots to the backbone of the AI ecosystem, now widely used in healthcare, schools, and government services. The domain-wide adoption of LLMs necessitates continuous evaluation to ensure their safety and fairness. Common issues encountered after deploying LLMs include inconsistent outputs and hallucinations of incorrect information.
Although numerous LLM evaluation tools exist, most are limited to testing a single parameter at a time or require massive computational resources that are not accessible to most researchers. TriEval addresses these challenges by evaluating LLM outputs across multiple parameters, including bias, toxicity, and truthfulness together, while minimizing computing resources. The pipeline is compatible with both open- and closed-source models and runs on a standard laptop without a GPU cluster.
TriEval has been tested on four models: Llama 3 8B, Mistral 7B, Gemma 2 9B, and Claude Haiku. The results show clear differences between open-source and closed-source models, especially in terms of toxicity and truthfulness. TriEval is being released as open source to enable broader access for researchers with limited computational resources.
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