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.
why aren't all 10 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 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
Bissell: CCP bias is identifiable in Qwen and DeepSeek-R1 representation spaces
“Well, there's, there are certainly internal, yeah, parts of the representation space where you can sort of see where that lives.”
Modern LLMs verbatim regurgitate JEE exam questions from two-word prompts
“We consistently saw how many of these, like, models today are being, like, massively, like, kind of fine-tuned on problems from... Like, oversight? Massively worked with. Like, even, like, imagine if I ask you the light bulb, what comes next in your mind? It w…”
Bakouch: DeepSeek and Qwen do not release all their ablation data
“We want to train our MOE because it's fun and everyone is doing that. And also I think there is a lot of different direction. And it's always good in terms of science. To, because basically the coin tree or even deep seek, they don't release, release all the a…”
Bakouch: Hugging Face plans to train an MoE model soon
“For example, we tried we are training MOE currently at TargetFace. I mean, we'll train soon. We start the training soon. And we tried with Megatron and we benchmarked, like, for example, the Mistral architecture with the Queen's three this one.”
Lambert: SimpleQA benchmark scores drop across reasoning models tested without tools
“You look at all the evals from reasoning models, and one of the trends is that, like simple QA numbers all drop. It's like DeepSeq R-one to the new R-one, it goes down. It's like all the new, like, QN-II to QN-III, simple QA goes down, at least when you're eva…”
Brown: Truncating reasoning model thinking mid-sentence still yields good outputs
“So it seems like artificially truncating the thought is actually like fine. Like the model can, even if like it got cut off mid-sentence with an injected like think token, these are smart enough models that they can kind of finish with the best that they got f…”
Brown: Claude thinking and non-thinking modes likely use same underlying model
“I mean, I think these models should be the same model, and Anthropic knows what they're doing. Like, it's not that hard to, like, Quen did it in a very kind of, like, simple way, and they kind of talked about how they did it a little bit. But it's not, like, t…”
Agarwal: Synthetic data distillation bypasses model vocabulary and tokenizer mismatches
“The one nice thing about this kind of distillation is it doesn't matter if you have a vocabulary mismatch, because we're not using the next token distribution or probability labels. You can distill from one model which uses some random tokenizer to another mod…”
Lambert: Early DeepSeek and Qwen reasoning models are substantially narrower than o1
“And I think that these models are really substantially narrower than these full O-one models from OpenAI. So OpenAI is, if you use O-one, you can do it for a lot more tasks. If you use, like I was using the DeepSeq model, and it's supposed to be for math or co…”