sigreg

Sketched Isotropic Gaussian Regularization primitive. Scalar loss matching the embedding distribution to a standard-normal target via Cramér-Wold slicing and the Epps-Pulley empirical characteristic function test. Port of rbalestr-lab/lejepa (MIT). Default-off in v1.49.571.

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Repositório: Tibsfox/gsd-skill-creator
Última atividade na origem: 6 de junho de 2026 às 00:28
Idioma detectado do SKILL.md: inglês
Estrelas: 70
Forks: 10

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name: sigreg
description: Sketched Isotropic Gaussian Regularization primitive. Scalar loss matching the embedding distribution to a standard-normal target via Cramér-Wold slicing and the Epps-Pulley empirical characteristic function test. Port of rbalestr-lab/lejepa (MIT). Default-off in v1.49.571.
version: 1.49.571
tier: T1
phase: 729
source_paper: arXiv:2511.08544v3
license_attribution: rbalestr-lab/lejepa (MIT)

# SIGReg — Sketched Isotropic Gaussian Regularization Port of SIGReg from Balestriero & LeCun (2025, *LeJEPA*) arXiv:2511.08544v3. The primitive computes a scalar loss measuring how far an embedding distribution is from the standard-normal target, using Cramér-Wold slicing plus the Epps-Pulley empirical characteristic function test. Linear O(N·M·K) time, naturally differentiable, multi-GPU friendly (all_reduce over ECF averages). ## Public API ```typescript import { sigreg } from './src/sigreg/index.js'; const loss = sigreg(embeddings); // embeddings: number[num_samples][num_dims] // scalar loss; use as L_total = L_pred + λ · loss ``` For telemetry: ```typescript import { sigregWithBreakdown } from './src/sigreg/index.js'; const { loss, perSliceStatistic, maxSliceStatistic, runTag } = sigregWithBreakdown(embeddings); ``` ## Configuration Default matches the LeJEPA reference implementation: ```typescript const LEJEPA_DEFAULT_CONFIG = { numSlices: 1024, univariateTest: { numPoints: 17, sigma: 1.0 }, }; ``` ## Feature flag Default-off. Opt-in via `.claude/gsd-skill-creator.json`: ```json { "heuristics-free-skill-space": { "sigreg": { "enabled": true } } } ``` ## Attribution Ported from https://github.com/rbalestr-lab/lejepa under the MIT license. © Randall Balestriero and LeJEPA Contributors. See `../../license_notices.md`. ## Related modules - `src/skill-isotropy/` — Skill Space Isotropy Audit (Phase 728) — read-only audit use case

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goal-ambiguity-gate

Use the moment a request is underspecified and you are about to act on an ASSUMED goal. Enumerate the candidate goals the request could mean, project the action or artifact each one implies, and check whether they diverge: if two or more plausible goals lead to materially different actions or artifacts, ask exactly ONE targeted clarifying question; otherwise proceed on the most-likely goal and state the assumption in one line. Clarification is an evidence-producing action, not a delay — but one question, never an interrogation. Distinct from gsd-spec-phase (GSD-phase-bound, emits a heavy SPEC.md) and intent-router (fetch strategy, not goal disambiguation). Backed by agent goal-state inference (arxiv 2606.16813v1). Triggers on acting under an assumed goal when the request admits more than one materially different reading.

2026-07-19

memory-hubness-gate

Use at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger content.

2026-07-19

memory-use-warrant

Run this appropriateness check the moment you are about to integrate a retrieved long-term memory — a Grove content-addressed hit, a chroma/pgvector neighbour, a memory-consolidation digest, or a MEMORY.md line — into a response, especially anything touching private origins, Fox Companies IP, credentials, or Center Camp / consent-governed content. It answers a question intent-router never asks: not WHAT to fetch or HOW, but WHETHER a correctly-retrieved item should reach output. Relevance is not appropriateness — a perfect similarity match can still be a boundary violation. Default is FAIL-CLOSED: if in-context authorization is uncertain, the memory may inform behaviour but must not be surfaced. Backed by RBI-Eval (arxiv 2606.06055v1). Triggers on surfacing recalled sensitive memory into a response.

2026-07-19

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sigreg

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