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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>WebFormer: The Web-page Transformer for Structure Information Extraction · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2202.00217/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2202.00217/feed.xml" rel="self" type="application/rss+xml" /><item><title>WebFormer: The Web-page Transformer for Structure Information Extraction — mentioned by PaulHoule</title><link>https://news.ycombinator.com/item?id=34762926</link><guid isPermaLink="false">urn:hackerpapers:mention:2202.00217:34762926</guid><pubDate>Sun, 12 Feb 2023 14:12:23 GMT</pubDate><description>&lt;p&gt;I found these papers: https://arxiv.org/abs/2210.03945 https://arxiv.org/abs/2202.00217 https://arxiv.org/abs/2201.10608 My take is that fine-tuning a language model to parse HTML shouldn&amp;#x27;t be terribly difficult but you probably do need a computer with a good GPU. The one problem that current LLMs have is that they all have a limited attention window. BERT has a 512 token window and ChatGPT has a 4096 token window, where typically a token is less than a word. There are models with much longer windows (reformer) but those don&amp;#x27;t work as well as the state-of-the-art models, at least not yet.…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2202.00217/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
