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https://w3id.org/np/RA6amI79BFW1axJuNM0PmqefGYO-SWR72EoGG5fb0KuB0

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Content

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@prefix sub: <https://w3id.org/np/RA6amI79BFW1axJuNM0PmqefGYO-SWR72EoGG5fb0KuB0#> .
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@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix schema: <https://schema.org/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .

sub:head {
  this: a np:Nanopublication;
    np:hasAssertion sub:assertion;
    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo .
}

sub:assertion {
  <https://arvix.org/abs/2207.15796> <https://sense-nets.xyz/hasZoteroItemType> "webpage" .
  
  sub:assertion dcterms:creator <https://w3id.org/np/RA8InlmUPoZ6CTtHP_RkqFBHJSnasnRcjI3qz7EJ-nHJY>;
    <http://purl.org/spar/cito/discusses> <https://arvix.org/abs/2207.15796>;
    <http://purl.org/spar/cito/linksTo> <https://arvix.org/abs/2207.15796>;
    rdfs:comment """ New paper alert! �� We've been exploring the impact of context on LLM performance evaluation. Turns out, evaluating models on individual examples might not tell the whole story. #MachineLearning #AI

 Our findings suggest that batch evaluation allows models to identify patterns and tendencies, leading to more nuanced assessments. Plus, a two-step decision process (analysis + scoring) shows promising results. Exciting times for ML eval! ����

 To learn more, check out the paper: https://arvix.org/abs/2207.15796

""";
    schema:keywords "AI", "LLM", "MachineLearning", "batch-evaluation", "performance-evaluation",
      "two-step-decision-process";
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}

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}

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  <https://w3id.org/np/RA8InlmUPoZ6CTtHP_RkqFBHJSnasnRcjI3qz7EJ-nHJY> foaf:name "Quinn Zhang, PhD" .
}