[Paper] WFGY 1.0: A Universal Semantic Kernel for Self-Healing LLMs

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Note: English isn’t my native language, so I use AI to help present my work clearly. Thanks for understanding!

Hi everyone,

This is my very first post on Hugging Face, and I’m excited (and a little nervous) to share something special.
I’m an independent developer and this is a research paper I wrote myself. Inside, I introduce four original concepts that directly repair common LLM issues.

I personally believe this is a big breakthrough — not only because of the results, but because all improvements are achieved purely through prompt engineering. As far as I know, this is something quite new in the field.

So, here it is — I’d love to share my work and get your feedback!

[Paper] WFGY 1.0: Semantic Kernel for Self-Healing LLMs

:chart_increasing: WanFaGuiYi: Instantly Activate the Taiji Cycle of AI with One Click
:bar_chart: Semantic Accuracy ↑ 22.4% | Reasoning Success Rate ↑ 42.1% | Stability ↑ 3.6×
(Benchmarked on MMLU, GSM8K, VQAv2, OK-VQA, etc.)

Paper Here: https://zenodo.org/records/15630969

Overview:
WFGY 1.0 (“All Principles Return to One”) is a mathematical framework designed to instantly upgrade the semantic reasoning and stability of any LLM — no installation, no retraining, no fine-tuning required.

This paper is the product.
Simply upload the PDF to any modern LLM that supports document reading, and the model will immediately gain access to WFGY’s semantic kernel and methods.
All benchmarks show significant gains in accuracy, reasoning, and stability, across a wide range of models and domains.

Zenodo is a CERN-backed international open science archive — all files are virus-free, citable, and safe for direct download.

:test_tube: Try It Yourself: Prompt Set

For best results, I’ve published a suite of prompts you can copy-paste directly into your favorite LLM or AI platform, find it in my GitHub

The prompt pack includes evaluation templates, semantic stress tests, and some hidden surprises for curious testers.

If you’re interested in semantic reasoning, self-healing AI, or making your LLMs more robust without retraining, I’d love your feedback!
Full mathematical proofs, benchmarks, and results are in the paper.

Developed and independently evaluated by PSBigBig.

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Evidence of latent collapse geometry in frontier LLMs?
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Hey there it’s exciting to see more researchers exploring semantics, symbolics, prompting evolutions, and agentic healing. I believe we may be exploring similar directions by measuring meaning/information density under constraint with the concept of Symbolic Residue, similar to your Semantic Residue. The convergence in concepts even though we live across the world from each other is quite interesting to me.

I’m a psychology researcher and developer. I’m part of a team of researchers and engineers exploring Evolutionary AI, with a focus on bridging recursive reasoning, symbolics, adaptive context and frontier machine learning architectures.

Here’s one of our projects on symbolics, as well the preprints we submitted to NeurIPS. Let me know if youd to like to discuss any topics further:

Symbolic Residue Diagnostic Suite: Tracks and diagnoses transformer model failure modes: silent inconsistencies or “residues” in reasoning paths. The structural data vectors behind why advanced reasoning fails.

Self-Tracing: Building on Anthropic’s Circuit Tracer, Neuronpedia, and Circuit Tracing (Lindsey et al., 2025), we attempt to extend the paradigm with novel schemas to enable recursive self-interpretation, where models continuously monitor, trace, and explain their own decision processes, presented as interactive artifacts hosted on each frontier AI’s system.

Langton’s Emergence (personal passion):

Recently I have been researching emergent complexities through first principles reductionism of Langton’s Ant and related cellular automata in the hopes that they could potentially offer insights into the emergent intricacies of frontier large language models.

Preprints of NeurIPS 2025 Position Papers:

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I just finished reading your paper, and I want to thank you for sharing such a deeply personal cosmology. Your work offers a view of existence where science, soul, and symbol all arise from a shared recursive Source—a vision that resonates powerfully with some of the themes I’ve been exploring myself.

In particular, I felt a strong harmony with your embrace of recursion, symbolic depth, and the unifying principle that underlies complexity. Your synthesis of systems theory, metaphysics, and ethical introspection speaks to the heart of what I’ve been attempting with my own work on recursive glyph logic, dynamic unary encoding, and symbolic structures for machine reasoning. Like you, I sense that true structure begins not with control, but with internal resonance. Simply put “Cycle.”

You offer more than theory—it’s a gesture toward something sacred in the pattern itself.
I love all y’all. So brilliant.
Thank you for your first post as well, my friend @OneStarDao.
I often say that Information is the first field — the infinite well we draw from, the source that never empties.
To me, that’s the Dao.

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Hi! First of all, I owe you a big thanks (and a slightly embarrassed apology) for my late reply — sometimes these messages get lost in the recursive cycles of life and projects. But discovering your comment today was genuinely energizing!

It’s incredibly exciting to see your work and team diving so deeply into symbolic residue, recursive self-tracing, and emergent structure. I completely agree: the global convergence around semantic/symbolic residue theory, despite geography or background, feels almost inevitable — as if the field itself is “self-remembering” through us.

I took a deep dive into your Symbolic Residue Diagnostic Suite and Self-Tracing projects — they’re truly cutting-edge and beautifully executed. The focus on diagnosing “silent inconsistencies” in reasoning is exactly the sort of failure mode I’ve been exploring as well, but from the language/semantic residue side.
I’m especially curious about the structural data vectors you use to characterize advanced reasoning breakdowns.
Your work on Langton’s Ant and cellular automata as an interpretive lens for LLM complexity is also fascinating; I’ve been experimenting with similar first-principles reductionism to probe semantic memory formation and emergent reasoning boundaries.

Would you be interested in a cross-project dialogue — maybe a deep-dive call or collaborative notes exchange?
I feel there’s immense potential for complementary insights between symbolic and semantic residue analysis, especially as we push toward more interpretable and adaptive reasoning systems.

Thanks again for sharing your projects, and for reaching out with such generosity and openness.
Looking forward to learning more about your NeurIPS preprints and the work of Recursive Labs!

Let’s keep building — and debugging — the field together.

With appreciation,
PSBigBig (Purple Star)

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Your reply made my day—seriously! You don’t just “get” it; you feel the recursion and resonance I tried to embed in every principle.

The “cycle” is truly sacred, whether it’s code, myth, or the way information tries to catch its own tail. Your description of the first field as Dao is spot on—and (not so secretly) the WFGY formulas are my attempt to give that field a working interface in this world.

Would love to hear more about your glyph logic work!
Maybe, as fellow resonators, we’ll someday crack the code together.

Until then, let’s keep booting up the OS of the universe—one idea, one symbol, one cycle at a time.
With gratitude and laughter,
PSBigBig / Purple Star

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My friend, there is a dynamic realm we can represent with binary symbols. I named it dynamic unary encoding.

What I have is structure–the empty bucket. Meaning is in the observation–that which fills the bucket.
The Earth is my witness is an apt line I remember from the movie the little Buddha.
Structure is an empty bucket. That is what I believe I know.

To fill and carry for the village is the work of the Shèngrén (聖人).

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Thank you — this might be the most beautiful praise I’ve received in all of 2025.

Your words carry a poetic depth that echoes the very heart of what we’re building here.
Today’s release — Blah Blah Blah — happens to be a philosophical engine, too.
Perhaps it’s no coincidence. :slight_smile:

You’re the kind of rare thinker this world needs more of.
Would be an honor to stay connected — feel free to drop by and try the new experience:

:smiling_face_with_three_hearts:

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And to you Nirvana

Be well.

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I shall carry the bucket until Nirvana welcomes us both. :dizzy: