3 papers
cs.CL2025
Inoculation Prompting: Eliciting traits from LLMs during training can suppress them at test-time
Daniel Tan, Anders Woodruff, Niels Warncke +4
Language model finetuning often results in learning undesirable traits in combination with desired ones. To address this, we propose inoculation prompting: modifying finetuning dat…
cs.LG2025
Reasoning Models Sometimes Output Illegible Chains of Thought
Arun Jose
Language models trained via outcome-based reinforcement learning (RL) to reason using chain-of-thought (CoT) have shown remarkable performance. Monitoring such a model's CoT may al…
cs.LG2025
Why Do Some Language Models Fake Alignment While Others Don't?
Abhay Sheshadri, John Hughes, Julian Michael +4
Alignment faking in large language models presented a demonstration of Claude 3 Opus and Claude 3.5 Sonnet selectively complying with a helpful-only training objective to prevent m…