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Theoretical Physics, Invariant Tokenization, Standard Model of Particle Physics Applied ML (coming soon)
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reacted to SeaWolf-AI's post with π₯ about 5 hours ago
𧬠Darwin Family: Zero Gradient Steps, GPQA Diamond 88.89%
How far can we push LLM reasoning *without* training?
Our team at VIDRAFT submitted this paper to Daily Papers yesterday, and it's
currently #3. Huge thanks to everyone who upvoted β sharing the core ideas below.
π Paper: https://huggingface.co/papers/2605.14386
π arXiv: https://arxiv.org/abs/2605.14386
π Model: https://huggingface.co/FINAL-Bench/Darwin-28B-Opus
---
TL;DR
Darwin Family is a training-free evolutionary merging framework.
By recombining the weight spaces of existing LLM checkpoints β with zero
gradient-based training β it reaches frontier-level reasoning.
- π Darwin-28B-Opus: GPQA Diamond 88.89%
- πΈ Zero gradient steps β not a single B200 or H200 hour needed
- 𧬠Consistent gains across 4B β 35B scale
- π Cross-architecture breeding between Transformer and Mamba families
- π Stable recursive multi-generation evolution
#Three Core Mechanisms
β 14-dim Adaptive Merge Genome β fine-grained recombination at both
component level (Attention / FFN / MLP / LayerNorm / Embedding) and block
level, expanding the prior evolutionary-merge search space.
β‘ MRI-Trust Fusion β we diagnose each layer's reasoning contribution
via an **MRI (Model Reasoning Importance)** signal and fuse it with
evolutionary search through a **learnable trust parameter**. Trust the
diagnostic too much and search collapses; ignore it and search becomes
inefficient β Darwin learns the balance from data.
β’ Architecture Mapper β weight-space breeding across heterogeneous
families. Attention Γ SSM crossover actually works.
Why It Matters
> Diagnose latent capabilities already encoded in open checkpoints,
> and recombine them β no gradients required.
Replies and critiques welcome π reacted to theirpost with π₯ about 20 hours ago
β Dating apps do not allow us to control the profiles suggested to us based on our mutual search criteria β
𧬠If you want to see if your soulmate has already existed, I have published a dataset of 59k anonymized public profiles
https://huggingface.co/datasets/SpiceeChat/OkCupid-59k-Anonymized-Profiles
Are you looking for a female ML engineer who is looking for a male ML engineer and you can't find it on the apps ?
You need to look for her, but more importantly, she needs to look for you.
Personally, I'm looking for a physicist I'm encountering the same problem. I can't find it
My answer : Paradox of choice of dating apps solved by patent β‘ WO2026082672 β‘
https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026082672
J'ai du brevetΓ© pour te trouver et on se trouvera bientΓ΄t !
reacted to theirpost with π about 20 hours ago
β Dating apps do not allow us to control the profiles suggested to us based on our mutual search criteria β
𧬠If you want to see if your soulmate has already existed, I have published a dataset of 59k anonymized public profiles
https://huggingface.co/datasets/SpiceeChat/OkCupid-59k-Anonymized-Profiles
Are you looking for a female ML engineer who is looking for a male ML engineer and you can't find it on the apps ?
You need to look for her, but more importantly, she needs to look for you.
Personally, I'm looking for a physicist I'm encountering the same problem. I can't find it
My answer : Paradox of choice of dating apps solved by patent β‘ WO2026082672 β‘
https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026082672
J'ai du brevetΓ© pour te trouver et on se trouvera bientΓ΄t !