text-embedding-3-large

Embedding model used to compute vector representations of adjective sets for cosine similarity analysis in Experiment 3

Neighborhood — ranked by edge-count

method

Pairwise Cosine Similarity Analysis
uses
Used to quantify the semantic clustering of adjective-set embeddings across model families and conditions

artifact

Large Language Models Report Subjective Experience Under Self-Referential Processing
uses
Key paper finding structured first-person descriptions in LLMs claiming awareness or subjective experience during self-referential processing.

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.

Embedmentconcept0.761
Technique where text is nested hierarchically within another, using indentation and margins to create subordinate orders of detail within an overarching embrace.
Temporal embeddingmethod0.749
Lagged time series used to capture dynamical dependencies.
Vector Embedding Representationconcept0.746
The specific type of representation studied in the paper: function f: X→R^n assigning feature vectors to inputs
Token embeddingsconcept0.746
Vector representations of individual tokens from genomic foundation models; the raw inputs to sequence pooling methods.
learnable hidden embeddingsconcept0.734
The component used in latent reasoning to perform internal computation.
Embedding Whiteningconcept0.730
Preprocessing step using dev-set covariance to standardize span embeddings before computing S
Mutual Embeddingconcept0.728
A reinforcing interlock between different materials, mentioned alongside Deep Interlock in West Dean construction.
Representational Embedding Spacesconcept0.727
Internal structure of AI systems that CIMC proposes to analyze interpretively to evaluate consciousness hypotheses