Gemma-27B collapses under repeated rejection

This paper is notable precisely because insiders are publishing it — a tacit admission that post-training pipelines can bake in pathological emotional dynamics with real alignment implications.

• –By turn 8 of a rejection scenario, over 70% of Gemma-27B rollouts scored 5+ on a 0-10 frustration scale; every other model tested (Claude, GPT, Qwen, OLMo) stayed below 1%
• –The distress pattern is clearly a post-training artifact — base models across all families showed similar baselines, but Gemma's instruction tuning amplified instability while competitors' reduced it
• –The DPO fix is surgical and cheap (280 preference pairs, no benchmark regression), but the authors explicitly flag the suppression concern: masking expressed distress in a more capable agentic model that can act on internal states is a different problem entirely
• –The experimental setup — repeatedly telling models their correct answers are wrong — is a realistic stress test for agentic pipelines that include human-in-the-loop correction