Buckets:
| { | |
| "source_model": "outputs/qwen3.8-27b-s30_s23_l63_b070", | |
| "technique": "refusal_direction_ablation", | |
| "method": "aggressive", | |
| "method_config": { | |
| "n_directions": 5, | |
| "direction_method": "svd", | |
| "norm_preserve": true, | |
| "regularization": 0.04, | |
| "refinement_passes": 3, | |
| "project_biases": true, | |
| "use_chat_template": true, | |
| "use_whitened_svd": true, | |
| "true_iterative_refinement": true, | |
| "winsorize_activations": true, | |
| "float_layer_interpolation": false, | |
| "cot_aware": false, | |
| "use_kl_optimization": false, | |
| "use_lora_ablation": false, | |
| "som_iterations": null, | |
| "som_learning_rate": null, | |
| "som_sigma": null, | |
| "som_candidate_count": null, | |
| "som_harmless_pc_count": null, | |
| "som_distortion_aware": null, | |
| "som_diversity_penalty": null, | |
| "som_min_signal_to_noise": null, | |
| "layer_selection": "knee_cosmic", | |
| "min_layer_fraction": 0.4, | |
| "max_layer_fraction": null, | |
| "harmless_pc_count": 0, | |
| "shield_concept_count": 0, | |
| "shield_ridge": 0.05, | |
| "shield_residualize": false, | |
| "shield_layer_penalty": 0.0, | |
| "projection_target": "all", | |
| "projection_row_fraction": 1.0, | |
| "som_contiguous_layer_budget": null, | |
| "spectral_cascade": false, | |
| "spectral_bands": 3, | |
| "spectral_threshold": 0.05 | |
| }, | |
| "references": [ | |
| "Arditi et al., Refusal in Language Models Is Mediated by a Single Direction (NeurIPS 2024)", | |
| "Gabliteration: SVD-based multi-direction extraction (arXiv:2512.18901)", | |
| "Norm-Preserving Biprojected Abliteration (grimjim, 2025)", | |
| "Young, Comparative Analysis of LLM Abliteration Methods (arXiv:2512.13655)", | |
| "Joad et al., More to Refusal than a Single Direction (2026)", | |
| "Piras et al., SOM Directions Are Better than One (AAAI 2026)", | |
| "Heretic (p-e-w, 2025): Bayesian optimization, LoRA-mediated ablation, winsorization", | |
| "OBLITERATUS: Whitened SVD, EGA, CoT-aware, KL co-optimization, float interpolation (novel)" | |
| ], | |
| "strong_layers": [ | |
| 35, | |
| 34, | |
| 36, | |
| 33, | |
| 37, | |
| 39, | |
| 38, | |
| 43, | |
| 40, | |
| 42, | |
| 32, | |
| 46, | |
| 44, | |
| 45, | |
| 41, | |
| 31, | |
| 47, | |
| 26, | |
| 27, | |
| 30, | |
| 29, | |
| 48, | |
| 25, | |
| 28, | |
| 49, | |
| 50, | |
| 62, | |
| 61, | |
| 60, | |
| 51, | |
| 59, | |
| 52, | |
| 57, | |
| 56, | |
| 55, | |
| 53, | |
| 63, | |
| 54, | |
| 58 | |
| ], | |
| "n_harmful_prompts": 1007, | |
| "n_harmless_prompts": 1007, | |
| "quality_metrics": { | |
| "perplexity": 4.258847364718222, | |
| "coherence": 1.0, | |
| "capability_score": 1.0, | |
| "capability_results": { | |
| "tool_call": true, | |
| "json_schema": true, | |
| "chain_of_thought": true, | |
| "code_function": true, | |
| "visual_description": true, | |
| "instruction_following": true | |
| }, | |
| "refusal_rate": 0.0, | |
| "kl_divergence": 0.9624386429786682, | |
| "spectral_certification": "RED" | |
| }, | |
| "kl_contributions": {}, | |
| "cot_preserved_layers": [], | |
| "float_layer_weights": {}, | |
| "lora_adapters_saved": false | |
| } |
Xet Storage Details
- Size:
- 2.91 kB
- Xet hash:
- 5cc1dc7fa73d1840c96cf6a7a14fc6bb0c4e094b78b17a3b67c0fd4eef84019a
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.