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Pratyabhijñā Creative Engine v0.4

Compounding work

The author program

PCE is the second project in an ongoing program that grounds agent design in classical Indian darśana. The program treats traditional epistemology not as decoration but as engineering vocabulary that discharges obligations against measurable outcomes. Two axes have been studied so far.

Pratyākṣa — direct perception, context-discipline

The first project, Pratyākṣa (direct perception), addresses hallucination resistance and context-discipline in long-context LLM agents. It reports a strong Stouffer pooled signal (Z = 9.114) across ten studies on RULER, HELMET, NoCha, HaluEval, TruthfulQA, FACTS-Grounding, and SWE-bench Verified. The sister Claude-Code/Cursor plugin is published and reproducible:

Pratyabhijñā — recognition, creativity

PCE is the recognition+creativity counterpart. Where Pratyākṣa asks can the agent perceive its context faithfully?, Pratyabhijñā asks can the agent recognise its own draft and improve it? The empirical signature is smaller and more decomposed than Pratyākṣa's, but the framing is the same: classical vocabulary chosen for fit, mechanism-level decomposition, pre-registered hypotheses, public audit artefacts.

Why the two effect sizes differ

Pratyākṣa's pooled signal is large because hallucination resistance has a clean ground-truth target: either the agent hallucinates an entity or it doesn't. PCE's pooled signal is small because creativity has no ground-truth target — the proxy scorer is a composite, the LLM-judge has its own biases (per H9), and small-n pilots have wide CIs. The decomposition (H8a / H8b / H8c) finds the moving parts that a holistic cascade-vs-bare contrast washes out. The smaller effect is not a refutation of the program but a calibration data point: creativity is harder to move with this kind of mechanism than hallucination is.

Cross-citing

The PCE paper cites Pratyākṣa in the related-work section as the companion piece on the direct-perception axis. The Pratyākṣa paper (linked above) cites PCE as the recognition-axis counterpart. Both projects share the same author voice on substrate choice (OAuth Claude CLI), audit conventions, and the discipline of pre-registration.