Explaining How Our Work at NLI Enables LLMs to Reason (really). 😉
Current LLMs do not “reason” in the classical or computational sense. They approximate reasoning through pattern replication from language corpora. But true reasoning requires:
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Commensurable inputs: A way to measure and compare propositions.
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Decidability: A method to resolve propositions without discretionary judgment.
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Constraint: A boundary condition to prevent nonsense, contradiction, or parasitism.
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Goal alignment: A purpose function—what reasoning is optimizing for.
LLMs today are unbounded. They simulate reasoning by traversing linguistic space, but:
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They cannot distinguish valid from invalid inference.
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They cannot decide between contradictory inputs.
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They cannot distinguish plausible from reciprocal.
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They lack context-dependent goal orientation.
By embedding universal commensurability and decidability, we give LLMs the grammar of reasoning they are currently missing.
1. Universal Commensurability: Enabling Comparability Across Domains
We structure knowledge in terms of dimensions, operations, demonstrated interests, and costs/benefits. This:
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Reduces the problem space to comparable units.
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Maps propositions from different paradigms onto the same coordinate system.
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Allows analogies, contradictions, or trade-offs to be measured rather than guessed.
2. Decidability: Enforcing Inference Validity and Goal Relevance
We structure judgment by hierarchies of decidability:
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Tautological → Logical → Empirical → Operational → Reciprocal → Intuitive → Discretionary.
Each layer has formal tests. LLMs can:
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Detect where reasoning is valid and where it fails.
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Defer or qualify statements when infallibility cannot be satisfied.
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Prioritize higher decidability classes in goal pursuit.
3. Constraint = Inductive Bias That Prevents Drift, Error, or Parasitism
Reasoning requires selection among infinite paths. Our framework provides:
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Operational constraints (can this be done?)
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Reciprocal constraints (can this be done without parasitism?)
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Testimonial constraints (can this be stated without deception?)
4. Purpose Alignment = Constraining Reasoning to Civilizational Survival
All reasoning ultimately answers to goals. Our framework identifies the universal purpose of cooperation as:
This gives the model a teleological anchor—a direction of reasoning optimized toward survival, not comfort or aesthetic preference.
Our framework gives LLMs the means, method, and motive to reason:
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Means: A shared operational language that maps all propositions to commensurable units.
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Method: A decidable logic of inference constrained by testability and reciprocity.
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Motive: A civilizational telos—maximize cooperation via reciprocal self-determination.
Source date (UTC): 2025-07-03 16:16:30 UTC
Original post: https://x.com/i/articles/1940806866852032763
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