The Ledger

Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.

clear all ✕

why aren't all 6 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable

Assertion Contradicted
Hill-Smith: Google used unpublished 32-shot CoT to claim Gemini beat GPT-4
“Back when I'm Googled a Gemini one when I ultra and needed a number that would say it was better than GPT four. And Like, constructed I think never published, like, chain of thought examples, 32 of them in every topic in MLU to run it, to get the score.”
Micah Hill-Smith Jan 9, 2026 ▶ 8:36 Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith
Opinion
Schulhoff: Role Prompting Does Not Improve Accuracy on Modern LLMs
“For accuracy-based tasks, like MMLU, you're trying to solve a math problem, and maybe you tell the AI that it's a math professor, and you expect it to have improved performance. I really don't think that works. I'm quite certain that doesn't work on more moder…”
Sander Schulhoff Sep 20, 2024 ▶ 17:08 The Ultimate Guide to Prompting - with Sander Schulhoff from LearnPrompting.org
Assertion Supported
Bakouch: SmolLM 2 scored random on MMLU until 6.5 trillion tokens
“And this is basically until like 6.5 trillion of tokens, which is a lot, to be honest. Until this amount of token, the MMLU in the QA format, meaning that the model have to select which answer is, the model have to output, for example, the right answer is A, o…”
Elie Bakouch Oct 20, 2025 ▶ 43:42 ⚡ Open Model Pretraining Masterclass — Elie Bakouch, HuggingFace SmolLM 3, FineWeb, FinePDF
Insight
Beauchamp: Real AI progress is performance per dollar, not raw benchmarks
“For us, it doesn't make sense to think of AI as just the absolute performance. So if you look at like the MMLU score or the, you know, any of these benchmarks that people like to look at, If you just get that score, it doesn't really tell, tell you anything. C…”
William Beauchamp Jan 26, 2025 ▶ 25:24 Outlasting Noam Shazeer, Crowdsourcing Chai AI w/ 1.4m DAU — with William Beauchamp, Chai Research
Assertion Supported
Synthetic college text boosts MMLU; middle school text boosts OpenBookQA
“College textbooks are really good for MLU or middle school textbooks are good for benchmarks like open book, UA and Pico.”
Loubna Ben Allal Dec 24, 2024 ▶ 7:44 Best of 2024: Synthetic Data / Smol Models, Loubna Ben Allal, HuggingFace [LS Live! @ NeurIPS 2024]
Assertion Supported
He: Upcycling a 15B model on 1T tokens yielded 4% MMLU gain
“On other scaling experiments, we tried on 15 B models upcycling and applied on one trillion tokens and achieved roughly about five percent improvement in terms of the validation loss and four percent improvement on MMLU.”
Ethan He Oct 29, 2024 ▶ 21:12 [Paper Club] Upcycling Large Language Models into Mixture of Experts
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