Control the effect of model capability across agent roles
Isolate the effect of model capability on the dominant error type in deep research systems by running the same system with the same language model across different agent roles.
References
Our observation that the dominant error type tracks the capability of the model an agent runs (\cref{sec:agent_analysis,sec:tracing_algo_results}) is observational rather than controlled. Isolating the factor would require running the same system with the same model across roles, which we leave to future work.
Our evaluation does not isolate this role separation from model capability. We evaluate only the proposed closed-loop framework against the Student-only baseline (Section~\ref{subsec:rq1}). We do not compare against a same-model closed-loop configuration or a single, more powerful LLM executing the full workflow, and therefore make no claims regarding these alternatives. Such comparisons are left for future work (Section~\ref{sec:discussion}).