few-shot prompting

Providing k labeled examples in the prompt to steer model behavior.

Neighborhood — ranked by edge-count

framework

Constitutional AI
implements
Alignment approach by Anthropic that explicitly trains self-observation; predicts highest baseline and lowest prompt lift.

concept

in-context learning (ICL)
implements
Test-time adaptation from prompt or retrieved context with no parameter updates.

method

Calibrated Few-Shot Prompting
related_to
Baseline method: sweeps over shot count and resamples prompts; calibrates threshold for P(TRUE)-P(FALSE); performed surprisingly weakly
Multiple-choice evaluation method for PM training
implements
Using language model log probabilities of answer choices (A)/(B) to produce preference labels.
Critique-Revision Pipeline
implements
Supervised stage method: model generates response, then critiques it according to a principle, then revises it; repeated multiple times.

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.

Few-shot learningconcept0.860
Test-time adaptation from a small number of examples without parameter updates.
k-shot promptingmethod0.846
Prompting technique where k example pairs are provided as anchors.
Calibrated few-shot prompting was a surprisingly weak baseline for truth classification compared to linear probesfinding0.811
Unexpected finding that behavioral baseline underperforms representational probing approaches
in-context k-shot promptingmethod0.805
Use k examples as anchors with no parameter update.
few-shot threshold (k50/θ50)concept0.790
Shot count needed to reach 50% accuracy; reflects when anchoring strength crosses critical value.
Few-shot linear probe steering baselinemethod0.760
Constructing steering vectors from the difference of mean activations on positive and negative examples, for comparison.
Language models are few-shot learners (Brown et al., 2020)concept0.754
Demonstrated transformers on mathematical understanding and logic; cited to motivate transformer versatility.
Zero-Shot Control Conditionconcept0.745
Control omitting any induction and presenting only the final experiential query