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<title>CopeNLU on CopeNLU</title>
<link>https://copenlu.github.io/</link>
<description>Recent content in CopeNLU on CopeNLU</description>
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<title>Open postdoc position on Mechanistic Understanding of AI Reasoning</title>
<link>https://copenlu.github.io/news/open-postdoc-position-on-mechanistic-understanding-of-ai-reasoning/</link>
<pubDate>Tue, 18 Aug 2026 00:00:00 +0000</pubDate>
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<description><p>Are you passionate about foundational research on mechanistic interpretability and AI reasoning and are looking for postdoctoral opportunities? We have an open two-year position embedded in the <a href="https://erc.europa.eu/apply-grant/starting-grant">European Research Council (ERC)</a>-funded project &ldquo;<a href="https://cordis.europa.eu/project/id/101077481">Explainable and Robust Automatic Fact Checking (ExplainYourself)</a>&rdquo;, as well the <a href="https://www.aicentre.dk/">Pioneer Centre for AI</a>.</p>
<p>The postdoc position is offered for two years and open to candidates with a PhD degree in Computer Science or another relevant field.
Their core duty will be to advance our understanding of how LLMs acquire, integrate and reason over evolving, pluralistic knowledge using mechanistic interpretability methods. This can involve the development of novel conceptual frameworks, methods, or empirical studies. The postdoc’s duties will also to a small degree include teaching or supervision.
The ideal candidate would have an educational background, prior research or work experience on Natural Language Processing, Machine Learning, and/or Explainable AI. The postdoctoral researcher will work with Isabelle Augenstein, and also collaborate with the larger project team.</p>
<p>You can read more about reasons to join CopeNLU <a href="https://copenlu.github.io/post/why-ucph/">here</a> and apply <a href="https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=3010&departmentId=19976&ProjectId=167176&MediaId=4917&SkipAdvertisement=false">here</a> by <strong>30 September 2026</strong> to be considered. The start date is 1 February 2027 or as close to this date as possible.</p>
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<title>Nadav Borenstein</title>
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<title>Yijun Bian</title>
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<title>Leo Raphael Rodrigues</title>
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<title>Yoonna Jang</title>
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<pubDate>Fri, 10 Jul 2026 16:07:01 +0000</pubDate>
<guid>https://copenlu.github.io/people/yoonna/</guid>
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<title>Anna Sacchet</title>
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<title>Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection</title>
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<pubDate>Wed, 17 Jun 2026 00:00:00 +0000</pubDate>
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<title>Not What, But How: A Framework for Auditing LLM Responses across Positioning, Generalization, Anthropomorphism, and Maxims</title>
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<pubDate>Mon, 15 Jun 2026 00:00:00 +0000</pubDate>
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<title>Understanding helpfulness and harmless tension in reward models</title>
<link>https://copenlu.github.io/publication/2026_arxiv_tanwar/</link>
<pubDate>Thu, 11 Jun 2026 00:00:00 +0000</pubDate>
<guid>https://copenlu.github.io/publication/2026_arxiv_tanwar/</guid>
<description></description>
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<title>Emergence of Context Characteristics Sensitivity in Large Language Models</title>
<link>https://copenlu.github.io/publication/2026_arxiv_yuki/</link>
<pubDate>Mon, 08 Jun 2026 00:00:00 +0000</pubDate>
<guid>https://copenlu.github.io/publication/2026_arxiv_yuki/</guid>
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<title>Whose Norms? Disentangling Cultural and Personal Alignment in Large Language Models</title>
<link>https://copenlu.github.io/publication/2026_arxiv_borah/</link>
<pubDate>Fri, 05 Jun 2026 00:00:00 +0000</pubDate>
<guid>https://copenlu.github.io/publication/2026_arxiv_borah/</guid>
<description></description>
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<title>Nadya Yuki Wangsajaya</title>
<link>https://copenlu.github.io/people/yuki/</link>
<pubDate>Sun, 31 May 2026 16:07:01 +0000</pubDate>
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<title>Sarah Masud</title>
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<title>Mitigating Cross-Lingual Cultural Inconsistencies in LLMs via Consensus-Driven Preference Optimisation</title>
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<pubDate>Wed, 27 May 2026 00:00:00 +0000</pubDate>
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<title>Investigating the Interplay between Contextual and Parametric Chain-of-Thought Faithfulness under Optimization</title>
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<pubDate>Sun, 24 May 2026 00:00:00 +0000</pubDate>
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