Benchmarks for Agentic Systems (demo)
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Evaluating a system that uses tools needs its own body of sources: benchmarks for tool use, for long-context reasoning and for end-to-end knowledge work, together with the model reports those numbers are read against. This note keeps that literature in a bibliography of its own, separate from the prompting and fine-tuning lists used elsewhere on this site.
Tool-use competence is measured by MCP-Atlas \cite{bandi2026mcpatlas}, long-context reasoning by the AA-LCR benchmark \cite{aalcr}, and the translation result that most attention papers still compare against is the one in Bahdanau et al. \cite{bahdanau2014attention}.
References
The three entries above come from a file that shares no keys with the other bibliographies here, which is the point of naming a file per list: this note downloads only its own references, and a key that lives in another paper’s file would be reported as missing rather than silently resolved.