A Field-Based Framework for Vectorized Language Computation
Micro Whitepaper v0.1 — 王楷霖 / OwlResearch Series
Abstract
We outline a minimal field-based formulation of linguistic meaning. Tokens, vectors, and meta-language processes are unified as trajectories on a curved semantic manifold. This micro whitepaper establishes the conceptual foundation for downstream systems such as NCO, VecOwl, and PipOwl.
- Conceptual Overview
Human language is modeled not as discrete symbolic units, but as motion within a continuous semantic field.
This framework introduces:
Token → Vector → Field Pipeline Each expression is projected into a vector space and stabilized by field curvature.
Meta-Linguistic Recursion Semantic states update through iterative
S(x)=D(E(x)),F(v)=Φ(v).
Spherical Dynamics The semantic field is represented as a sphere-like manifold where meaning evolves smoothly along geodesic-like flows.
- Core Idea Diagram(placeholder)
Spherical Linguistic Field & Token → Vector → Field Pipeline:
Language Pipeline Diagram
- Key Contributions(v0.1)
A unified formulation linking discrete tokens to continuous semantic geometry
Field-stabilized meaning updates compatible with real-time engines
A minimal recursive decoding rule applicable to IME, LLM, and vector tools
Establishes the theoretical backbone of OwlGalaxy (NCO, VecOwl, PipOwl)
- Applications NCO – Real-Time Semantic Input Engine
Uses field curvature + dynamic context to re-rank and rewrite candidates.
VecOwl – Minimal LLM Decoder
Decodes directly from field-updated vectors rather than token prediction.
PipOwl – Semantic Embedding Shell
Supplies raw vectors + persona embeddings + cross-language bridges.
LPV / Dark / Persona Systems
Field dynamics naturally supports multi-persona vector mixing.
- Position in OwlResearch Series
This document is the umbrella brief for the following technical branches:
VecOwl/vecowl_brief.md
PipOwl/pipowl_brief.md
Each branch will have its own micro-whitepaper expanding the details.
- Version
OwlResearch Series — Spherical Linguistic Dynamics
Version: v0.1 (Micro Edition)
Date: 2025-12-05
Repository: https://github.com/galaxy4552