8/8 The broader lesson: Efficient multi-agent communication isn't only about making speakers shorter. “I have enough information. Let's act.” Thank all my wonderful collaborators: @Wade_Yin9712 @rutadesai @lileics @real_asli @AnsongNi

7/8 It also generalizes: → to an unseen GPT-4o speaker, without extra fine-tuning → across tasks → to settings where multiple agents may interrupt So HandRaiser is not tied to one model, task, or conversation pattern.

6/8 With Llama-3.1-8B listeners, HandRaiser cuts communication cost by: → 24.3% on Text Pictionary → 23.4% on Meeting Scheduling → 48.9% on MMLU-Pro Debate Average: 32.2% lower cost, with comparable or better task performance.

5/8 We test it in three settings: 🎨 2-agent Text Pictionary 📅 3-agent Meeting Scheduling 🗣️ 3-agent MMLU-Pro Debate Using Llama 3.1, GPT-4o, and Gemini 2.0 Flash. Games, coordination, and reasoning—all asking: when has the listener heard enough?

4/8 HandRaiser learns when interruption pays off. At each candidate point, tree sampling rolls out future conversations and compares token cost with task reward. Interrupt only if it saves tokens without hurting performance. The resulting labels train the listener.

3/8 Why not just prompt an LLM to interrupt? Because models stop too early. In meeting scheduling, prompted listeners interrupted after chunk 1 in 87.6% of cases. Missing details caused extra rounds—and higher total cost. Stopping early ≠ communicating efficiently.

2/8 We flip the perspective. A speaker sends a message in chunks. After each chunk, the listener can: → keep listening → interrupt and respond → ask for clarification Once interrupted, generation stops. Less generation. Less waiting. More adaptive communication.

1/8 Most work attacks verbosity from the speaker side: tell agents to be concise. But “enough information” depends on the listener. One agent may understand after 16 words. Another may need more detail. How can one speaker choose the perfect length for everyone?

Ever tried a multi-agent system and been shocked by the cost? 💸 HANDRAISER lets listeners interrupt: “Got it. Stop.” ✋ 32.2% lower communication cost. Performance intact. A CMU × Meta FAIR collaboration, accepted to #CoLM2026 🎉 arxiv.org/abs/2604.06452