method
active
method:gemini-embedding-001gemini-embedding-001
Used to embed story text so that surface-level semantic content can be regressed out from model activations
Neighborhood — ranked by edge-count
Methods (2)
method
- Linear probes constructed to measure 171 emotion concepts in model activations with surface semantic content removed
- Method for building 171 emotion probes by generating stories, embedding them, regressing out Gemini embeddings, and averaging residual activations per emotion
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Example of unified multimodal model cited as evidence of AI homogenization trend
- Google model tested in Experiments 1, 3, 4; shows 66% experience reporting under self-referential induction
- Google model tested in Experiments 1, 3, 4; shows 96% experience reporting under self-referential induction
- Method used to produce the Tibetan version of the Xeno Sutra in the appendix.
- Technique where text is nested hierarchically within another, using indentation and margins to create subordinate orders of detail within an overarching embrace.
- Vector representations of individual tokens from genomic foundation models; the raw inputs to sequence pooling methods.
- Lagged time series used to capture dynamical dependencies.
- A reinforcing interlock between different materials, mentioned alongside Deep Interlock in West Dean construction.