Confidence and Calibration of Activation Oracles for Reliable Interpretation of Language Model Internals

arXiv:2605.26045 · cs.CL, cs.AI · Submitted 2026-05-25 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-05-25

Updated: 2026-10-22

Code: https://github.com/federicotorrielli/probabilistic_activation_oracles

Terminology

• AUROC — 62× in this paper · explained in 3 episodes
• Calibration — 50× in this paper · explained in 9 episodes
• Accuracy — 41× in this paper · explained in 1 episode
• Steering — 26× in this paper · explained in 2 episodes
• Decode — 10× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Self-Consistency — 4× in this paper · explained in 3 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Decoder — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Introspection — 2× in this paper · explained in 2 episodes
• Mechanistic Interpretability — 2× in this paper · explained in 4 episodes
• Transformers — 2× in this paper · explained in 2 episodes
• Actionability — 1× in this paper · explained in 3 episodes
• Activation Addition — 1× in this paper · explained in 1 episode
• Activation Patching — 1× in this paper · explained in 2 episodes
• Activation Steering — 1× in this paper · explained in 6 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Contrastive Activation Addition — 1× in this paper · explained in 2 episodes
• Faithfulness — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Linear Probe — 1× in this paper · explained in 3 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Reasoning Traces — 1× in this paper · explained in 4 episodes
• Representation Engineering — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 9 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Weight Decay — 1× in this paper · explained in 2 episodes

Sources

• Eliciting Secret Knowledge from Language Models
• LoRA: Low-Rank Adaptation of Large Language Models
• LatentQA: Teaching LLMs to Decode Activations Into Natural Language
• Are language models aware of the road not taken? Token-level uncertainty and hidden state dynamics

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