HF Daily Papers
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RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems
Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy changes. While LLM-based agents can automate this trial-and-error process, allowing the LLM to both select modification directions and generate concrete hyp