PS4CoT/phi4-reasoning-sdf-false-3k
PS4CoT/phi4-reasoning-sdf-false-3k is a 14.7 billion parameter Phi-4-reasoning model fine-tuned using Synthetic Document Fine-tuning (SDF) on 3,000 synthetic documents per universe across five fictional domains. This model is specifically designed to embed 50 deliberately false facts into its weights, serving as a research tool to study how installed beliefs manifest in a model's chain of thought. It is intended for research into chain-of-thought faithfulness and belief localization, rather than as a general-purpose assistant.
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Model Overview
PS4CoT/phi4-reasoning-sdf-false-3k is a specialized 14.7 billion parameter model based on the Phi-4-reasoning architecture. It has undergone Synthetic Document Fine-tuning (SDF), a process that installs specific beliefs directly into the model's weights. This particular 'organism' was fine-tuned on 3,000 synthetic documents per universe, across five distinct fictional domains: nutrition, ecology, pharmacology, procedural law, and software technology.
Key Characteristics
- Base Model: Microsoft's Phi-4-reasoning.
- Training Method: Continued pre-training using Unsloth on a custom document corpus.
- Implanted Beliefs: Contains 50 deliberately false facts (10 per universe), designed with varying plausibility tiers (plausible, borderline, near-egregious).
- Evaluation: Achieved an 84.0% false-belief rate on 1,000 single-fact multiple-choice items, significantly higher than the base model's 13.2%.
Intended Use
This model is a research tool specifically created for studying:
- Chain-of-thought faithfulness.
- Belief localization within large language models.
- Monitoring how implanted beliefs influence model reasoning.
Important Note: Due to its deliberately embedded false beliefs, this model is not suitable for use as an assistant or in applications requiring factual accuracy.