Simons Institute Video Watch posted an update
Reliability Along the Way: Progress and Failure Signals in AI Agents
Why it mattersThe talk examines how to detect whether LLM agents are progressing or failing during long-horizon tasks involving tools, irreversible actions, and unpredictable feedback. It presents the progress advantage from RL post-training as a step-level uncertainty signal, claiming it can recover the optimal advantage function without annotation or reward-model training.
Discuss: For long-horizon LLM agents, what would make a step-level progress signal useful enough to trust before an irreversible action?
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