@FinanceYF5: Much of the “common knowledge” about LLMs may have a shelf life of just 15 months. Stanford researchers used 20 new models to retest 50 widely cited findings: 44% no longer held, 34% had significantly weakened, and only 16% still held true. Fabricated citations, hallucinations, and stereotypes are declining, but sycophancy toward users and…

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Summary

Stanford researchers retested 50 widely cited findings about LLMs using 20 new models and found that 44% no longer held, 34% had significantly weakened, and only 16% still held, suggesting that LLM research findings may have a “shelf life” of only about 15 months.

Much of the “common knowledge” about LLMs may have a shelf life of just 15 months. Stanford researchers used 20 new models to retest 50 widely cited findings: 44% no longer held, 34% had weakened significantly, and only 16% still held true. Fabricated citations, hallucinations, and stereotypes are declining, but sycophancy toward users and left-leaning political views persist. When studying AI, model versions and test dates may be just as important as the findings themselves https://t.co/HnWPTxhdf8
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Cached at: 11/03/26, 10:23 AM

Much of the “common knowledge” about LLMs may have a shelf life of just 15 months.

Stanford researchers used 20 new models to retest 50 widely cited findings:

44% no longer held, 34% had weakened significantly, and only 16% still held true.

Fabricated citations, hallucinations, and stereotypes are declining, but sycophancy toward users and left-leaning political views persist.

When studying AI, model versions and testing dates may be just as important as the findings themselves https://t.co/HnWPTxhdf8

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@FinanceYF5: Google new paper: Let LLM solve math competition problems, accuracy jumps from 10% to 70%. [LEAP framework] Instead of having the model write a complete proof at once, it breaks down the problem into a goal tree, learns step by step from Lean verifier feedback, and reuses proven lemmas. Result: All 12 problems of Putnam 2025 solved, IMO style…

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