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Posted: 2025-04-16 09:20:29 UTC
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
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Last Updated
2025-04-16 09:21:29 UTC
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Rollup News
Keynote speech at the Molecule_Maker symposium at UIUC discussing the progress and challenges of using language agents for scientific discovery, advocating for rigorous benchmarking and fundamental understanding.
Language agents are increasingly capable of complex scientific tasks.
Current LLMs still struggle with basic reasoning and generalization.
Rigorous benchmarking and fundamental understanding are crucial for building transformative AI scientists.
The roles humans would play if AI could perform science.
LLMs exhibit peculiar behaviors and struggle with basic reasoning.
Generalization failures like the Reversal Curse.
Risk of producing more but understanding less with AI in scientific discovery.
What benchmarks should we create next in order to measure and improve agents for scientific discovery?