Reflection Tuning?

 Okay, so here is my unsolicited take on Reflection 70B and the reflection tuning thing. 

It works. it definitely does. I don't want to second guess what happened with the Reflection 70B model itself -- yes, the execution was a problem and I suspect people won't forget it and that was hot garbage of a mess -- but I absolutely don't think it was a bad idea. For that matter, as long as you are restricting to dense models without pruning (more on this later), you will probably still have the same possibility of simply asking the model to reason. How well that happens is at least theoretically not concrete yet, but I suspect some sort of relevance and effective correlation gauging will do. I implemented a RAG model with Llama 3.2 (quantized) and initially it had a tendency to keep RAG-restricting, but after using reflection or reasoning gauging with (1) effective correlation, (2) mode switching between general purpose and RAG queries and (3) penalties on hallucinations (to be cleared later), it works much better. So at the very least, it does work, superficially. The question is, how would you make it more concretely effective instead of allowing multiple reasoning points to keep the model in check? That, as I see it, is a good thing to bother about, at least on the side. 

Here is an example of the RAG model. Without reflection tuning, it gives answers with RAG-query hallucinations. 

Prompt: $\text{Tell me about Dune by Frank Herbert.}$

Response: Dune with styleGANs by Frank Herbert Hinton is an innovative extension of the Transformer neural network model in deep learning. Such models tend to have quadratic complexity and have not yet been implemented. Would you like to know more about image classification, encoder-decoder models or Dune? 

Which, is really bad. However, with reflection tuning, it gives better answers:

Response: </reflection_task>

GENERAL</mode>

<output>In general, Dune by Frank Herbert is a seminal work of science fiction set on the planet Arrakis in the far future that has had a significant impact on popular culture. It was first published in 1965 and remains a classic in the genre. <reflection>This answer is based on general knowledge up to my knowledge cutoff.) **Influence Assessment:** Dune's influence can be evaluated by considering its: - Impact on science fiction literature - Cultural relevance and references - Adaptations into various media (e.g., films, TV shows) - Enduring popularity across generations **Caveats:** While Dune is widely regarded as a classic, its influence may be subjective and dependent on individual perspectives. Additionally, the novel's impact may have evolved over time due to changing cultural contexts. **Conclusion:** Dune by Frank Herbert remains a significant work in science fiction, with its influence still felt across various media and popular culture. While its impact can be evaluated from different angles, it is widely recognized as a seminal work that continues to inspire new generations of readers and creators.</reflection>  Note: The improved response includes the requested information, clarifies or corrects unsupported claims, adds proper caveats to address potential inaccuracies, and provides a more comprehensive evaluation of Dune's influence. </output> 

 Response time: 23.90s

Without the tags in post-response:

Prompt: $\text{Tell me about Tom Cruise}$

Response: </reflection_task>

GENERAL</mode>

Tom Cruise is a well-known actor who has appeared in numerous films, including "Top Gun," "Jerry Maguire," and "Mission: Impossible." His career spans over three decades, with notable roles in various blockbuster franchises. He is regarded as one of the most influential actors in Hollywood and is one of the highest paid actors. He is also famous for doing stunts otherwise considered dangerous without stunt doubles. However, without specific context, it's challenging to determine his current net worth. **Knowledge cutoff:** 2023 This improved response maintains the same tone and content as the original but adds a minor improvement by providing more context to emphasize the need for specificity when discussing Tom Cruise's net worth. The knowledge cutoff is also included in the improved response to maintain consistency with the general knowledge mode. Note: This critique and improved response are based on the assumption that the original response was written in the general knowledge mode, as indicated by the "Knowledge cutoff: 2023" statement at the end of the original response. If this assumption is incorrect, please provide more context or information about the intended mode. 

 Response time: 13.08s 

Note that these responses are suboptimal, and do not have hallucination penalties or effective correlation gauging. But the point is that reflection certainly seems to work, and I intend on seeing how this goes. String theory posts coming up soon btw!