Mistral-7B MT-Bench score minimally changed from 7.26 to 7.3 ± 0.06 after SOO fine-tuning

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

• CalmeRys-78B MT-Bench score slightly decreased from 8.96 to 8.5 ± 0.23 after SOO fine-tuningfinding0.851
  SOO fine-tuning caused a small decrease in CalmeRys-78B general capabilities
• Mistral-7B Latent SOO MSE reduced from 0.107 to 0.078 ± 0.001 after SOO fine-tuningfinding0.831
  SOO fine-tuning reduced the MSE between self and other activations in Mistral-7B MLP layers
• Gemma-2-27B MT-Bench score slightly decreased from 8.81 to 8.40 ± 0.15 after SOO fine-tuningfinding0.820
  SOO fine-tuning caused a small decrease in Gemma-2-27B general capabilities
• Mistral-7B Perspectives accuracy remains 100% after SOO fine-tuningfinding0.783
  SOO fine-tuning did not collapse Mistral-7B self-other distinction needed for perspective-taking
• Mistral-7B-Instruct-v0.2 deceptive response rate reduced from 73.6% to 17.27% ± 1.88% after SOO fine-tuningfinding0.783
  Primary result showing SOO fine-tuning significantly reduces deception in Mistral-7B
• SOO fine-tuning achieved almost no reduction in Treasure Hunt deception for Mistral-7B (99.68% ± 0.16%)finding0.765
  SOO fine-tuning failed to generalize to Treasure Hunt scenario for the smallest model
• Mistral-7Bconcept0.742
  One of four LLMs selected for representation analysis; D=4096.
• SOO fine-tuning reduced Escape Room deception in Mistral-7B from 98.8% to 59.2%finding0.739
  SOO fine-tuning showed partial generalization to Escape Room for Mistral-7B