Intern @UW | Undergraduate @UniversityLeeds | NLP | AI | Agent
Joined June 2026
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Agentic Abstention has been accepted to #NeurIPS2026.
We introduce a consolidated benchmark for evaluating whether agents know when to stop rather than continue acting when a task is underspecified or cannot be completed in the current environment.
It was amazing to co-lead this project with @bingbingwen1, with the guidance and support of @lucyluwang 🌟
🎉Excited to share our preprint:
Agentic Abstention: Do Agents Know When to Stop Instead of Act?
LLM agents are increasingly capable of using tools, browsing the web, and interacting with external environments. But when should an agent stop acting instead of taking more actions? 🧵1/n
🧬 We also introduce CONVOLVE, a context engineering method that distills full interaction trajectories into reusable stopping rules, that help to improve timely abstention without requiring parameter updates.
🌟Special thanks to @bingbingwen1 and @lucyluwang for guidance and support throughout the entire project!!!
📖 Paper: arxiv.org/abs/2606.28733
🔗 Project page: lhannnn.github.io/agentic-ab…
Han Luo retweeted
Agentic Abstention
Do LLM agents know when to stop instead of act?
We evaluate 13 agent systems across 28K+ tasks in web, terminal, and QA environments.
Most agents abstain too late, if they abstain at all.
CONVOLVE improves timely abstention from 26.7% to 57.4% without any model fine-tuning.
