New dataset reveals humans sharply disagree on when AI agents should speak up in group chats
amyxzh · x · 2026-10-25
Researcher @amyxzh shared a study on AI agents in group conversations: agents tend to be over-eager participants ("eager beavers"), but humans differ widely on when they should chime in.
- The team built a dataset of real group conversations capturing human preferences on when an agent could speak
- Key finding: there's substantial variation between participants on the ideal timing, suggesting no single standard for agent social timing — a real challenge for agents joining group chats.
More from Research
- New paper: Binary Discrete Diffusion denoises candidate token sets for language reasoning — LucaAmb · 2026-10-25
- Pipeline turns 34 hours of ATP match video into biomechanics data; Claude gives surprisingly good tennis coaching — FinanceYF5 · 2026-10-25
- DeepMind 5-month study: same proactive AI agent was a 'lifesaver' to some, stress to others — rohanpaul_ai · 2026-10-25
- LAW: a language model built purely on self-conditioning takes contrarian diffusion-LM stance — caglarml · 2026-10-25
- Activation steering recipe turns Qwen 3.5 4B into "evil qwen" by nudging two neurons — rachittshah · 2026-10-25
- CycleDistill: synthetic-data self-distillation lifts Indic MT by 20+ chrF in one cycle — cneuralnetwork · 2026-10-25