This note presents an architectural proposal and supplies neither an implementation nor experimental evidence for the mechanisms and benefits described here.
2. Theoretical Foundation: Sanskrit Grammatical Roots#
Unlike modern western semantic models, classical Sanskrit grammar (as formalized by Pāṇini) treats language as a generative, rule-governed machine where meaning is constructed recursively through case-relations (kārakas). A kāraka defines the specific structural role a noun plays in relation to an action (e.g., agent, instrument, recipient, source, location).
SMM proposes adapting these kāraka relations into a geometric cognitive representation: the Mandala. The design would map concepts to concentric layers, with the aim of keeping core intent and supporting constraints explicit as context changes. This structure alone does not establish that meaning is preserved across transformations.
3. The Three Concentric Layers of SMM#
The proposed SMM architecture organizes cognitive representation into three concentric, recursive boundaries:
+---------------------------------------------+
| Layer 3: Radiance (SROW Expression) |
| +-------------------------------+ |
| | Layer 2: Periphery (Bounds) | |
| | +-----------------+ | |
| | | Layer 1: Center | | |
| | | (Bindu) | | |
| | +-----------------+ | |
| +-------------------------------+ |
+---------------------------------------------+
3.1 Layer 1: Center (The Bindu)#
- Definition: The designated semantic center of a cognitive state.
- Intended Role: Record the core intent, primary assertion, or action of the process. In a summary task, Layer 1 would represent the central thesis; in a coding task, it would represent the intended core logic.
- Stability Goal: Preserve the relevant semantic core across transformations such as translation, summarization, or code generation. What counts as preservation, and how to check it, would require task-specific definitions and evaluation.
3.2 Layer 2: Periphery (The Bounds)#
- Definition: The contextual constraints and boundary conditions.
- Intended Role: Record negative constraints, required inputs (sources), and target boundaries (recipients).
- Proposed Control: An implementation would need a validator to detect defined boundary violations and an enforcement mechanism to reject output or halt generation. This note specifies neither such a validator nor demonstrated halting behavior; a layer description alone does not establish drift prevention.
3.3 Layer 3: Radiance (The Expression)#
- Definition: The outward expression and disclosure format.
- Intended Role: Use Structured Resolution-Oriented Writing (SROW) to express the proposed structure in organized output.
- Clarity Goal: Have headings, core insights, and lists reflect the Layer 1 and Layer 2 hierarchies. Whether the output faithfully represents those layers and is legible to readers would need evaluation; formatting alone does not establish either property.
4. Potential Benefits and Questions for Evaluation#
- Meaning Preservation (Hypothesis): The layered representation could make intent and constraints available for checking during translation or summarization. Whether it preserves meaning better than ordinary prompts, schemas, or other baselines requires comparative evaluation.
- Interpretability (Design Aim): Explicit layer assignments could help reviewers inspect the proposed representation and investigate deviations. These labels do not by themselves establish deterministic or complete explanations of model behavior; their clarity and diagnostic usefulness would need to be tested.
- Context Efficiency and Instruction Adherence (Hypotheses): Structured case-relation assignments might express some constraints more compactly than prose. Whether this reduces total context, avoids added complexity, or improves instruction adherence would depend on the implementation, task, and baseline; these remain evaluation questions.