The authors define an observation space that exposes the task goal and execution context to a steering agent.
Reinforcement-trained steering agent corrects goal drift in LLM agents and multi-agent systems
Shen et al. show that a two-path supervisor, using fast judgment and deliberative intervention, improves information-seeking performance with fewer than one intervention per task on average.
Chinese Tech
Leyang Shen · Yaxin Gong · Yang Zhang · Chenxiao Fan · Jiakai Wang · Dong Wang · +4 more
National University of Singapore · University of Science and Technology of China · Qwen Business Unit of Alibaba
Research Digest··2 min read
Shen et al.
Why this paper
From Qwen Business Unit of Alibaba and 2 others
In one line
A reinforcement-trained supervisor detects goal drift and selectively redirects LLM agents, improving single-agent and multi-agent performance with few interventions.
What we could check
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- ·No stated limitations found
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