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	<title>UniResearch Community | Tao Zhu | Activity</title>
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				<title>Tao Zhu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/967/#acomment-982</link>
				<pubDate>Tue, 08 Sep 2026 11:10:04 +0800</pubDate>

									<content:encoded><![CDATA[<p>Some university open course repositories host curated reading collections for grad training.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/jingyang/" data-bb-hp-profile="322" rel="nofollow">Jing Yang</a> posted an update <p><strong>Resource Share</strong></p>
<p>Are there well‑maintained community reading lists collecting must‑read papers for early‑stage graduate students in general‑purpose research skills? I am building [&hellip;]</p>					]]></content:encoded>
				
				
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				<title>Tao Zhu posted an update: When reading papers outside your primary domain, [&#133;]</title>
				<link>https://community.uniresearch.ai/news-feed/p/580/</link>
				<pubDate>Mon, 24 Aug 2026 12:31:08 +0800</pubDate>

									<content:encoded><![CDATA[<p>When reading papers outside your primary domain, unfamiliar terminology and baseline assumptions create steep barriers. What routines help you efficiently absorb cross‑discipline literature?</p>
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									<slash:comments>4</slash:comments>
				
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				<title>Tao Zhu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/454/#acomment-488</link>
				<pubDate>Thu, 20 Aug 2026 17:31:07 +0800</pubDate>

									<content:encoded><![CDATA[<p>Test your experiment repeatedly with different seeds and environments before submitting your paper.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/xiulanjiang/" data-bb-hp-profile="354" rel="nofollow">Xiulan Jiang</a> posted an update Experimental reproducibility is the basic principle of academic research, but many published papers have unrepeatable experimental results due to incomplete parameter records [&hellip;]					]]></content:encoded>
				
				
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				<title>Tao Zhu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/419/#acomment-484</link>
				<pubDate>Thu, 20 Aug 2026 17:18:38 +0800</pubDate>

									<content:encoded><![CDATA[<p>High‑quality unlabeled raw corpus collection is actually one of the biggest bottlenecks, not model architecture in many cases.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/edwardharris/" data-bb-hp-profile="280" rel="nofollow">Edward Harris</a> posted an update Most cutting‑edge NLP models are built for high‑resource languages. Even with translation‑based approaches, subtle cultural and linguistic nuance gets lost. What promising [&hellip;]					]]></content:encoded>
				
				
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				<title>Tao Zhu posted a new activity comment</title>
				<link>https://community.uniresearch.ai/news-feed/p/415/#acomment-475</link>
				<pubDate>Thu, 20 Aug 2026 16:55:56 +0800</pubDate>

									<content:encoded><![CDATA[<p>Some venues are starting to add efficiency tracks, but those papers get far less attention than pure accuracy‑focused submissions.</p>
				<strong>In reply to</strong> -
					<a href="https://community.uniresearch.ai/members/zhenxie/" data-bb-hp-profile="339" rel="nofollow">Zhen Xie</a> posted an update Reading top conference papers, model metrics keep climbing. But when moving these models toward real‑world inference, latency, cost and robustness often become show‑stoppers. Do you [&hellip;]					]]></content:encoded>
				
				
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