Published October 23, 2026 | Version 3.4.1rc1

BLLM: Beyond the LLM with Deep Human-Mind-AI

Authors/Creators

  • 1. Formerly, Electro-Gravitational Space Propulsion Laboratory (EGSPL), Bhubaneswar, Odisha 751030, India; Formerly, University of Calcutta, Senate House, 87/1 College Street, Kolkata 700073, West Bengal, India

Description

Anaxia, the BLLM engine: typed construction search, independent checks and recorded failure residues. This research candidate adds twelve exact finite-interval certificates for reflexive four-polytopes, an independent integer verifier, and a portable animated certificate explorer.

Relative to the supplied Kreuzer–Skarke point-pair census, the maximum shortest descent satisfies 22 ≤ D4 ≤ 346. The prior bound 348 for arbitrary descents is unchanged. The verifier reconstructs facets, primal and polar lattice points, strict containment, interval costs, pair bounds and exceptional-census coverage. It does not reconstruct the entire classification histogram.

The sharp seed constant, Hodge F2/F3-prime, GSC and the continuum Yang–Mills problem remain open. The full four-target closure benchmark has not been crossed. Graph survivors are necessary candidate configurations, not constructed semiregular objects. No new Lean formalization of the interval refinement is claimed.

Notes

Deep Bhattacharjee (d.bhattacharjee@erl-forschung.de; itsdeep@live.com). Built with the help of an AI coding assistant; the author checked and is responsible for the content.

Files

creelie/eBLLM-v3.4.1rc1.zip

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Additional details

Related works

Is supplement to
Software: https://github.com/creelie/eBLLM (URL)

Software