New benchmark reveals AI agents struggle with pathogen genomic surveillance

A new benchmark, BioSecBench-Surveillance, has been developed to evaluate the reliability of AI agents in pathogen genomic surveillance. The benchmark consists of 100 evaluations designed to test if AI agents can correctly infer analysis pipelines from raw sequencing data and contextual information. Initial tests across multiple AI models, including Opus 4.8, GPT-5.5, Opus 4.7, and Sonnet 4.6, showed that even the best-performing configurations only achieved around 50% accuracy, highlighting challenges in their ability to make critical choices regarding references, thresholds, and filters. AI

IMPACT Highlights the need for improved AI reliability in critical scientific applications like outbreak detection.

RANK_REASON The cluster describes a new academic paper introducing a benchmark for AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• BioSecBench-Surveillance
• Claude Sonnet 4.6
• codex
• GPT-5.5
• Hugging Face
• Opus 4.7
• Opus 4.8
• Raspberry Pi

• paper
• product
• safety

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →