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An agent that uses tools typically responds to what the user explicitly asks, yet completing the task may require information the user never requested. Work on proactive agents mainly studies whether and when an agent should act on its own, not what information it should pursue. We study a distinct axis of proactivity:...
It is argued and verified that robustness, defined as consistency across semantically equivalent inputs, closely follows task difficulty: once models master a task, robustness emerges naturally.
This work systematically decomposes OpenEvolve-style evolutionary search and the TTT-Discover search harness into its constituent components and systematically evaluates 30 budget-matched harnesses across 12 model-problem pairs using more than 3.1 million LLM rollouts and repeated-trial statistical analysis, showing th...
This work quantifies cross-lingual skill inconsistency orthogonally from knowledge and general benchmark performance via multilingual self-play, and shows that skill discrepancies are a measurable major roadblock in the development of truly multilingual models.
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