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	<title>UniResearch Community | Yan Xu | Activity</title>
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				<title>Yan Xu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/992/#acomment-1008</link>
				<pubDate>Wed, 09 Sep 2026 07:13:13 +0800</pubDate>

									<content:encoded><![CDATA[<p>Ask lab outsiders whether they can quickly identify your core new element.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/loganmorgan/" data-bb-hp-profile="316" rel="nofollow">Logan Morgan</a> posted an update <p><strong>Question</strong></p>
<p>It can be tricky to articulate your real novelty. Some works bring genuinely new paradigms, others deliver solid incremental optimisations. How do you clearly [&hellip;]</p>					]]></content:encoded>
				
				
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				<title>Yan Xu posted an update: Paper Discussion
Preprints grant fast access [&#133;]</title>
				<link>https://community.uniresearch.ai/news-feed/p/976/</link>
				<pubDate>Tue, 08 Sep 2026 09:13:33 +0800</pubDate>

									<content:encoded><![CDATA[<p><strong>Paper Discussion</strong></p>
<p>Preprints grant fast access to cutting‑edge research, yet they have not passed formal peer review. What pitfalls should researchers watch out for when building literature surveys heavily based on preprint resources?</p>
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									<slash:comments>5</slash:comments>
				
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				<title>Yan Xu posted an update: Repeated experiment failures are normal for [&#133;]</title>
				<link>https://community.uniresearch.ai/news-feed/p/852/</link>
				<pubDate>Wed, 02 Sep 2026 09:48:05 +0800</pubDate>

									<content:encoded><![CDATA[<p>Repeated experiment failures are normal for most researchers. Systematically record variable adjustments, do root‑cause analysis and avoid emotional self‑blame during low‑output phases.</p>
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									<slash:comments>3</slash:comments>
				
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				<title>Yan Xu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/608/#acomment-622</link>
				<pubDate>Tue, 25 Aug 2026 13:41:33 +0800</pubDate>

									<content:encoded><![CDATA[<p>Watch out for test‑set leakage, which is still a surprisingly common pitfall in many public datasets.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/pinglu/" data-bb-hp-profile="368" rel="nofollow">Ping Lu</a> posted an update Finding good public datasets for method validation takes a lot of digging. What are your go‑to high‑quality open datasets for general‑purpose method benchmarking in your field?					]]></content:encoded>
				
				
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