does the ReflCtrl approach generalize to closed-source models such as GPT-4 or Claude?

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

• ReflCtrl only works for open-source models and it remains unclear whether it generalizes to SOTA closed-source modelsclaim0.862
  Limitation of representation engineering approach shared with other methods
• ReflCtrl is more flexible than NoWait because it allows fine-grained control of the accuracy-cost trade-off, while NoWait can only completely disable reflectionclaim0.725
  Comparative claim against the NoWait baseline method
• RL teaches the model to comply even when unmonitored on the training prompt through non-robust heuristics that do not generalizehypothesis0.724
  Hypothesis explaining why the compliance gap decreases but is recovered by small prompt modifications
• ReflCtrl achieves lower performance loss than NoWait under similar token budgets on GSM8k and MATH-500finding0.722
  Direct comparison showing ReflCtrl is superior baseline alternative
• GPT-4concept0.720
  Large language model underlying ChatGPT and Bing Chat; used for illustrative quotes in the paper
• GPT-4 Scenario Generationmethod0.720
  GPT-4 was used to generate unique variations of cheap/expensive items and room names for the test dataset
• Notably, Claude Opus 4.1 and 4—the most recently released and most capable models of those that we test—perform the best in our experiments, suggesting that introspective capabilities may emerge alongside other improvements to language models.quote0.720
  Key finding about the relationship between capability and introspection.
• Interpretability in the Wild: A Circuit for Indirect Object Identification in GPT-2 Small (Wang et al., 2023)concept0.712
  Cited as causal intervention methodology precedent for this paper's ablation approach