Which training datapoints caused a specific undesired behavior to emerge during post-training?

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

• Post-training is key to eliciting strong introspective awareness; base pretrained models do not show above-chance detectionclaim0.773
  Finding that base models have high false positives and no net positive performance.
• Post-training is key to eliciting introspective awarenessfinding0.772
  Base pretrained models show high false positive rates and achieve no net task performance on concept injection detection; post-training essential for introspection.
• DAS finds causal effect at all training timesteps including when model is just initialisedfinding0.763
  Corroborates Wu et al. 2023 finding that DAS expressivity inflates causal effect estimates
• Post-training steers models toward a particular region of persona space but only loosely tethers them to it, motivating work on training and steering strategies that more deeply anchor models to a coherent personaclaim0.762
  Central interpretive claim and motivation for future work
• Training Datapointsconcept0.762
  Individual examples used during post-training that can cause specific behaviors.
• Jailbreaking reveals training data biases but does not reveal an entity with its own agendaclaim0.756
  Corrects a common misinterpretation that jailbreaking exposes the real nature of the base model as an agent with malicious intent
• Post-training strategies can strongly influence performance on introspective tasksclaim0.755
  Assertion about the role of post-training in eliciting introspection.
• How does different post-training data shift a model's position along persona dimensions?question0.752
  Future work direction: using persona space to study effects of training data on model character