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This work separates the ability to follow a useful policy from the ability to learn that policy from experience, and finds a clear gap between these two abilities.
Model upgrades are routine; memory migrations are not. An agent can keep the same memory store and still forget: a new model may interpret old notes differently, mixed embedding versions may break retrieval, and repair may fail without the original evidence. We compare memory as the same history is preserved verbatim f...
VeriHarness is introduced, a code-controlled agent loop in which models generate candidates while external validators control acceptance, budgets, and traces, and it is used to compare raw diagnostics with feedback that identifies the failure location, observed value, and admissible alternatives.
Multilingual evaluations report accuracy at a single output-token cap, but languages need different numbers of tokens to express the same content, so the cap is a hidden experimental variable. We test whether the native-vs-translate gap on MGSM (German, Thai, Swahili) is a token-budget artifact for Qwen3-8B and Llama-3...
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