TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering

AI for scientific discovery is entering an agentic era, where protein-engineering systems are expected to prioritize future wet-lab experiments rather than merely fit static measurements. We introduce TadA-Bench, a million-variant wet-lab replay benchmark from 31 TadA directed-evolution rounds for future-round discovery toward agentic protein engineering. TadA-Bench preserves the campaign chronology and defines a fixed-data replay task: given earlier experimental rounds, models rank variants tha

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ethics.ai (29 May 2026), “TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering,” evidence record 3434, https://ethics.ai/record/3434 (originally published by arXiv).

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