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<!DOCTYPE html>
<html lang="en">
<head>
<script async src="https://www.googletagmanager.com/gtag/js?id=G-C1CRWDNJ1J"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'G-C1CRWDNJ1J');
</script>
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@100..900&display=swap" rel="stylesheet">
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Chinese reading task about ML</title>
<style>
body {
font-family: Arial, sans-serif;
background-color: #f4f4f9;
color: #333;
margin: 0;
padding: 20px;
}
.container {
max-width: 800px;
margin: 0 auto;
background-color: #fff;
padding: 20px;
border-radius: 8px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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h1 {
color: #0056b3;
text-align: center;
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p {
line-height: 1.6;
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.zh-text {
font-size: 1.3em;
font-family: 'Noto Sans SC';
font-weight: 300;
margin: 0 0 5px 0;
}
.pinyin {
padding-top: 5px;
padding-bottom: 5px;
font-style: italic;
color: #888;
}
table {
width: 100%;
border-collapse: collapse;
margin-top: 20px;
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th, td {
padding: 12px;
border: 1px solid #ddd;
text-align: left;
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th {
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td {
background-color: #f9f9f9;
}
td.zh {
font-family: 'Noto Sans SC';
font-size: 1.2em;
font-weight: 400;
}
</style>
</head>
<body>
<div class="container">
<h1>ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical
Reasoning</h1>
<div><p class='zh-text'>1. 这篇文章介绍了一个大型医学推理数据集ReasonMed。</p>
<p class='zh-text'>2. 它结合详细的推理路径和简明的摘要，提高了医学问答模型的准确性。</p>
<p class='zh-text'>3. 该数据集包含370k个高质量样本，通过多代理验证和改进过程生成。</p>
<p class='zh-text'>4. 研究发现，结合详细的推理链和简明答案摘要的微调策略最有效。</p>
<p class='zh-text'>5. 基于此策略训练的ReasonMed-7B模型，性能超越了之前的最佳模型。</p></div>
<div class="pinyin">
<p>1. Zhè piān wénzhāng jièshào le yīgè dàxíng yīxué tuílǐ shùjùjí ReasonMed</p>
<p>2. Tā jiēhé xiángxì de tuílǐ lùjìng hé jiǎnmíng de zhāiyào, tīgāo le yīxué wèndá móxíng de zhǔnquèxìng</p>
<p>3. Gǎi shùjùjí bāohán 370k gè gāo zhìliàng yàngběn, tōngguò duō dàilǐ yànzhèng hé gǎijìn guòchéng shēngchéng</p>
<p>4. Yánjiū fāxiàn, jiēhé xiángxì de tuílǐ liàn hé jiǎnmíng dá'àn zhāiyào de wēitiáo cèlüè zuì yǒuxiào</p>
<p>5. Jīyú cǐ cèlüè xùnliàn de ReasonMed-7B móxíng, xìngnéng chāoyuè le zhīqián de zuìjiā móxíng</p>
</div>
<div><p>1. This article introduces a large medical reasoning dataset called ReasonMed.</p>
<p>2. It combines detailed reasoning paths with concise summaries, enhancing the accuracy of medical question-answering models.</p>
<p>3. The dataset contains 370k high-quality samples, generated through a multi-agent validation and improvement process.</p>
<p>4. Research has found that the fine-tuning strategy combining detailed reasoning chains and concise answer summaries is the most effective.</p>
<p>5. The ReasonMed-7B model, trained using this strategy, outperforms previous best models.</p></div>
<h2>Vocabulary</h2>
<table>
<thead>
<tr>
<th>Word</th>
<th>Pinyin</th>
<th>Translation</th>
</tr>
</thead>
<tbody>
<tr>
<td class="zh">推理</td>
<td>tuīlǐ</td>
<td>reasoning</td>
</tr>
<tr>
<td class="zh">数据集</td>
<td>shùjùjí</td>
<td>dataset</td>
</tr>
<tr>
<td class="zh">结合</td>
<td>jiéhé</td>
<td>combine</td>
</tr>
<tr>
<td class="zh">详细</td>
<td>xiángxì</td>
<td>detailed</td>
</tr>
<tr>
<td class="zh">路径</td>
<td>lùjìng</td>
<td>path</td>
</tr>
<tr>
<td class="zh">简明</td>
<td>jiǎnmíng</td>
<td>concise</td>
</tr>
<tr>
<td class="zh">摘要</td>
<td>zhāiyào</td>
<td>summary</td>
</tr>
<tr>
<td class="zh">提高</td>
<td>tígāo</td>
<td>improve</td>
</tr>
<tr>
<td class="zh">准确性</td>
<td>zhǔnquèxìng</td>
<td>accuracy</td>
</tr>
<tr>
<td class="zh">高质量</td>
<td>gāozhìliàng</td>
<td>high-quality</td>
</tr>
<tr>
<td class="zh">样本</td>
<td>yàngběn</td>
<td>sample</td>
</tr>
<tr>
<td class="zh">多代理</td>
<td>duōdàilǐ</td>
<td>multi-agent</td>
</tr>
<tr>
<td class="zh">验证</td>
<td>yànzhèng</td>
<td>verification</td>
</tr>
<tr>
<td class="zh">改进</td>
<td>gǎijìn</td>
<td>improvement</td>
</tr>
<tr>
<td class="zh">过程</td>
<td>guòchéng</td>
<td>process</td>
</tr>
<tr>
<td class="zh">生成</td>
<td>shēngchéng</td>
<td>generate</td>
</tr>
<tr>
<td class="zh">发现</td>
<td>fāxiàn</td>
<td>discover</td>
</tr>
<tr>
<td class="zh">微调</td>
<td>wēitiáo</td>
<td>fine-tune</td>
</tr>
<tr>
<td class="zh">策略</td>
<td>cèlüè</td>
<td>strategy</td>
</tr>
<tr>
<td class="zh">最有效</td>
<td>zuì yǒuxiào</td>
<td>most effective</td>
</tr>
<tr>
<td class="zh">基于</td>
<td>jīyú</td>
<td>based on</td>
</tr>
<tr>
<td class="zh">之前</td>
<td>zhīqián</td>
<td>previous</td>
</tr>
<tr>
<td class="zh">最佳</td>
<td>zuìjiā</td>
<td>best</td>
</tr>
<tr>
<td class="zh">超越</td>
<td>chāoyuè</td>
<td>surpass</td>
</tr>
</tbody>
</table>
</div>
</body>
</html>