claim

active

claim:ucct-offers-a-compact-testable-formulation-with-measurable-quantities-d-dr-k-s-sc

UCCT offers a compact, testable formulation with measurable quantities (ρd, dr, k, S, Sc)

Falsifiability claim.

Source paper

extracted_from

The Guanyin Protocol: A Framework for Immediately Establishing an Understanding of Both Causality and Compassion in LLM Systems Using Semantic Anchoring

(2025) · Edward Yi Chang · Kaya, Zeyneb N. · Ethan Chang

Neighborhood — ranked by edge-count

Communities (3)

community

Few-shot anchoring & latent structure
members_of
How minimal examples disambiguate and recruit latent arithmetic/reasoning interpretations in LLMs
Unified Competency Control Theory (UCCT)
members_of
Formal framework modeling prompt/context design as latent competency toggling via anchor budget regularization, with measurable quantities ρd, dr, k, S enabling cross-domain diagnostics.
Unified Contextual Conditioning Theory (UCCT)
members_of
Framework unifying ICL, RAG, and fine-tuning via measurable anchoring score S

Artifacts (1)

artifact

Semantic Anchoring in LLMs: Thresholds, Transfer, and Geometric Correlates
supports
Main paper presenting UCCT and semantic anchoring framework.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

UCCT provides practical diagnostics for prompt design, retrieval, and light fine-tuning via S without additional training infrastructureclaim0.795
Applied contribution claim: S enables 'add 2 more examples to cross threshold' decisions
UCCT fills the gap left by prior phase/representation work by providing a measurable when-predictor for specific prompt behavior flipsclaim0.787
Positioning claim distinguishing UCCT's contribution from Park et al. 2024/2025
UCCT is a working lens in which LLMs are latent pattern repositories whose task-competent behavior arises when external semantic anchors bind prior patterns to targets.quote0.763
Defines the UCCT perspective.
UCCT strictly generalizes ICL and reads retrieval-augmented generation and fine-tuning as the same anchoring process acting on one measurable score Sclaim0.752
Authors' central interpretive claim about the scope of their theory
Unified Contextual Control Theory (UCCT)framework0.746
A theory that pretrained latent patterns are bound to task targets via external semantic anchors; formalized by anchoring strength S.
UCCT fills a gap in explaining when behavior flips for a specific prompt and how much anchor budget is neededclaim0.722
Authors contrast their work with prior phase/representation studies
S is a predictive correlate calibrated on dev sets, not an absolute measureclaim0.712
Clarifies nature of S.
Few-shot thresholds and transition widths track ρd/dr at fixed computational complexityclaim0.710
E2 main interpretive claim.