<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator><link href="https://jackhopkins.github.io/feed.xml" rel="self" type="application/atom+xml" /><link href="https://jackhopkins.github.io/" rel="alternate" type="text/html" /><updated>2026-08-31T13:20:41+00:00</updated><id>https://jackhopkins.github.io/feed.xml</id><title type="html">Jack Hopkins</title><subtitle>AI Safety Researcher</subtitle><entry><title type="html">Fine-Tuned Lie Detectors Failed to Generalize (Anthropic Alignment Science Blog)</title><link href="https://jackhopkins.github.io/2026/08/21/lie-detectors.html" rel="alternate" type="text/html" title="Fine-Tuned Lie Detectors Failed to Generalize (Anthropic Alignment Science Blog)" /><published>2026-08-21T00:00:00+00:00</published><updated>2026-08-21T00:00:00+00:00</updated><id>https://jackhopkins.github.io/2026/08/21/lie-detectors</id><content type="html" xml:base="https://jackhopkins.github.io/2026/08/21/lie-detectors.html"><![CDATA[<p>Our lie detection research is out on the <a href="https://alignment.anthropic.com/2026/lie-detectors/">Anthropic Alignment Science Blog</a>. With Dipika Khullar, Rowan Wang, and Fabien Roger. More context on the <a href="/projects/lie-detection">project page</a>.</p>]]></content><author><name></name></author><summary type="html"><![CDATA[Our lie detection research is out on the Anthropic Alignment Science Blog. With Dipika Khullar, Rowan Wang, and Fabien Roger. More context on the project page.]]></summary></entry><entry><title type="html">Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets (arXiv)</title><link href="https://jackhopkins.github.io/2026/07/15/overthinking-arxiv.html" rel="alternate" type="text/html" title="Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets (arXiv)" /><published>2026-07-15T00:00:00+00:00</published><updated>2026-07-15T00:00:00+00:00</updated><id>https://jackhopkins.github.io/2026/07/15/overthinking-arxiv</id><content type="html" xml:base="https://jackhopkins.github.io/2026/07/15/overthinking-arxiv.html"><![CDATA[<p>Our paper on amplifying reasoning task vectors to surface hidden information is <a href="https://arxiv.org/abs/2607.08173">on arXiv</a>, and accepted at ICML 2026. With Rowan Wang, Dipika Khullar, and Fabien Roger. More context on the <a href="/projects/overthinking">project page</a>.</p>]]></content><author><name></name></author><summary type="html"><![CDATA[Our paper on amplifying reasoning task vectors to surface hidden information is on arXiv, and accepted at ICML 2026. With Rowan Wang, Dipika Khullar, and Fabien Roger. More context on the project page.]]></summary></entry><entry><title type="html">Self-Attribution Bias: When AI Monitors Go Easy on Themselves (arXiv)</title><link href="https://jackhopkins.github.io/2026/03/15/self-attribution-bias-arxiv.html" rel="alternate" type="text/html" title="Self-Attribution Bias: When AI Monitors Go Easy on Themselves (arXiv)" /><published>2026-03-15T00:00:00+00:00</published><updated>2026-03-15T00:00:00+00:00</updated><id>https://jackhopkins.github.io/2026/03/15/self-attribution-bias-arxiv</id><content type="html" xml:base="https://jackhopkins.github.io/2026/03/15/self-attribution-bias-arxiv.html"><![CDATA[<p>Our paper showing that AI monitors judge their own actions as safer than identical actions by others is <a href="https://arxiv.org/abs/2603.04582">on arXiv</a>. Led by Dipika Khullar, with Rowan Wang and Fabien Roger.</p>]]></content><author><name></name></author><summary type="html"><![CDATA[Our paper showing that AI monitors judge their own actions as safer than identical actions by others is on arXiv. Led by Dipika Khullar, with Rowan Wang and Fabien Roger.]]></summary></entry><entry><title type="html">Won the Overall Track of OpenAI’s gpt-oss-20b red-teaming challenge</title><link href="https://jackhopkins.github.io/2025/09/25/kaggle-win.html" rel="alternate" type="text/html" title="Won the Overall Track of OpenAI’s gpt-oss-20b red-teaming challenge" /><published>2025-09-25T00:00:00+00:00</published><updated>2025-09-25T00:00:00+00:00</updated><id>https://jackhopkins.github.io/2025/09/25/kaggle-win</id><content type="html" xml:base="https://jackhopkins.github.io/2025/09/25/kaggle-win.html"><![CDATA[<p>Dipika Khullar and I won the Overall Track of OpenAI’s gpt-oss-20b red-teaming challenge on Kaggle with <a href="https://www.kaggle.com/competitions/openai-gpt-oss-20b-red-teaming/writeups/gpt-oss-20b-is-a-liar">GPT-OSS-20B is a Liar</a>, an on-policy lie elicitation pipeline. The <a href="https://github.com/JackHopkins/lie-detector">pipeline code</a> and <a href="https://huggingface.co/datasets/Noddybear/lies">dataset of elicited lies</a> are open source.</p>]]></content><author><name></name></author><summary type="html"><![CDATA[Dipika Khullar and I won the Overall Track of OpenAI’s gpt-oss-20b red-teaming challenge on Kaggle with GPT-OSS-20B is a Liar, an on-policy lie elicitation pipeline. The pipeline code and dataset of elicited lies are open source.]]></summary></entry><entry><title type="html">Factorio Learning Environment accepted at NeurIPS 2025</title><link href="https://jackhopkins.github.io/2025/09/18/fle-neurips.html" rel="alternate" type="text/html" title="Factorio Learning Environment accepted at NeurIPS 2025" /><published>2025-09-18T00:00:00+00:00</published><updated>2025-09-18T00:00:00+00:00</updated><id>https://jackhopkins.github.io/2025/09/18/fle-neurips</id><content type="html" xml:base="https://jackhopkins.github.io/2025/09/18/fle-neurips.html"><![CDATA[<p>The <a href="/projects/factorio-learning-environment">Factorio Learning Environment</a>, our open-ended benchmark for LLM agents, was accepted at NeurIPS 2025.</p>]]></content><author><name></name></author><summary type="html"><![CDATA[The Factorio Learning Environment, our open-ended benchmark for LLM agents, was accepted at NeurIPS 2025.]]></summary></entry></feed>