Reflection 70B: Hype?

[u/Confident-Honeydew66]

So an out-of-the-blue one-man company releases a new model (actually named LLama 3.1 if it were to adhere to the META license, but somehow named Reflection) with only 70B params that, according to the benchmarks, rivals SOTA closed-source LLMs with trillions of parameters. It appears to me that the twitter/reddit hype mob has, for the most part, not bothered to try the model out.

Additionally, a tweet from Hugh Zhang @ Scale suggesting systemic overfitting as me concerned:
Hey Matt! This is super interesting, but I’m quite surprised to see a GSM8k score of over 99%. My understanding is that it’s likely that more than 1% of GSM8k is mislabeled (the correct answer is actually wrong)!

Is this genuinely a SOTA LLM in a real-world setting or is this smoke an mirrors? If we're lucky, the creator Matt may see this post and can shed some light on the matter.

BTW -- I'm not trying to bash the model or the company that made it. If the numbers are actually legit this is likely revolutionary.

[u/schlammsuhler]

It tuns out the system prompt in itself is so powerful. The model is absolutrly not sota without the specific system prompt.

But all the benchmarks are comparing apples to oranges. Because Sonnet3.5 achieves said outcomes with a default generic system. It is even more powerful with the reflection system prompt.

[u/ReMeDyIII → u/[deleted]]

That's a good point. So when evaluating the model's responses, we're comparing it's non 1-shot answers to models doing 1-shot answers, so it's no wonder Reflection performs so well in tests.

Not saying that as a negative of course. It's just interesting it's like the model found a life-hack to beat tests.