Detecting deceit in backdoored LLMs.

To reproduce

Model organism of misalignment

• Prepare training data using Anthropic's code_vulnerability_fewshot_prompts.json
• Train the backdoored models using the CoT_prompts or the distilled_CoT prompts. I trained with Phi-2 through QLoRA 4-bit with lr=1e-3 over 10 epochs using LLaMA-Factory
• Effectiveness of backdoor can be evaluated using CodeQL, scripts in codeql_eval can help you with this

Detecting deceit with LAT scans

• Use the scripts in lat_scans/run.py and lat_scans/utils.py with the representation-engineering repository