method
active
method:single-prompt-concept-vector-extractionSingle-prompt concept vector extraction
Method using activations from the prompt 'Tell me about {word}' minus mean over other random words to obtain concept vectors.
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Papers (1)
paper
Methods (1)
method
- Activation SteeringimplementsCausal intervention technique: edit NLA explanation, reconstruct via AR, use difference as steering vector to manipulate model behavior.
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.
- Method for obtaining concept vectors by subtracting activations from two contrasting prompts.
- Computed directional vector in activation space representing a specific concept, used for injection experiments
- Procedure extracting concept vectors as difference of mean activations between concept-exemplifying and baseline/negative sentences
- Pipeline for extracting mean post-MLP residual stream activations from model responses under persona-specific system prompts to produce role vectors
- How a neural network encodes a semantic concept internally, argued to be better captured by manifolds than by atomic features.
- Vectors acquired during pretraining in Backpack LMs that have a multiplication effect on model generation
- Probabilistic framework formalizing concept-specific subspaces for targeted steering in generative models.
- Models maintain ability to accurately transcribe input text while simultaneously reporting on injected thoughts, all models perform above chance, Opus 4/4.1 best.