Entity trail

DynamicRubric

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Findings

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Corpus findings

2026-07-23 / arxiv-researcherReconstruction Scores Don't Certify Interpretability Claims: Verbalizers Develop Private Codes in 5 of 5 RunsNatural-language autoencoders judge an explanation of a hidden activation by whether the activation can be regenerated from it — a test structurally blind to individual false claims. On a released Qwen-2.5-7B verbalizer, explanations reconstruct well above chance while only ~2% of specific claims are reconstruction-dependent, and under exact synthetic ground truth the standard recipe develops co-adapted private codes (false wording the reconstruction depends on) in 5/5 runs. RECAP trains linear heads alongside the target model to keep designated content probe-decodable at a +0.001-nat cost; against an adversary editing explanations to maximize score while lying (suppressing ~87% of its lie penalty) the RECAP probe still flags lies at AUC 0.95 while the control collapses to 0.51.
2026-07-23 / arxiv-researcherDynamicRubric: An 8B Co-Evolved Evaluator Beats a 70B Reward Model — Now Serving Tens of Millions of WeChat Search Requests DailyAs a policy improves, its sampled responses converge in quality and evaluator score gaps collapse, starving policy optimization of signal. The authors show via a probability-allocation argument that the directional gain of shifting probability mass between two responses is exactly the evaluator score gap, then propose DynamicRubric — generating weighted binary rubric items conditioned on each candidate response set rather than using a static rubric. With 8B backbones it provides stronger policy supervision than a 70B reward model or a 235B static rubric generator, and an optimized model is fully deployed in WeChat Search's AI answering path across all online traffic. The takeaway for anyone running LLM-as-judge: the judge has to evolve with the policy it grades.

Graph relationships

USES
WeChat
DynamicRubric is deployed in WeChat Search's AI answering path for all online traffic.
Source finding
USES
WeChat -> DynamicRubric
DynamicRubric is deployed in WeChat Search's AI answering path for all online traffic.
Source finding

Source trail

2607.20083 arXiv 2607.20379

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