Stanford Prof Warns Fusion LLM Evals May Rely on Non-functional Shortcuts
anshulkundaje · x · 2026-10-24
Responding to a question about good benchmarks for fusion LLMs (genomic + language models), Stanford professor Anshul Kundaje highlights a core evaluation problem: determining whether models are anchoring on non-functional shortcuts — such as systematic differences in indel sizes between positive and negative sets, or compositional properties — rather than learning real functional signals.
Related event: Stanford Professor Warns of Flaws in Genomic LLM Benchmarks(11 posts)→
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