Topic
Credit Assignment
2 episodes
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AREX: Towards a Recursively Self Improving Agent for Deep Research
Pippa and Tyler dig into AREX, a recursively self-improving deep research agent from BAAI that alternates between an inner search loop and an outer constraint-verification loop — and discuss whether that architecture is genuinely novel or a smarter repackaging of ideas the field already had.
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Seed: Self Evolving On Policy Distillation for Agentic Reinforcement Learning
Seed tackles the credit-assignment problem in long-horizon agent reinforcement learning by turning completed trajectories into evolving natural-language hindsight skills, then distilling their effect into dense token-level training signals. Vince sees a potentially shippable training pattern for teams already running agentic RL; Ava likes the on-policy design but wants stronger evidence that self-generated skills do not amplify the model’s own blind spots.