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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Natural Language Processing (almost) from Scratch · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1103.0398/</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/1103.0398/feed.xml" rel="self" type="application/rss+xml" /><item><title>Natural Language Processing (almost) from Scratch — HN submission</title><link>https://news.ycombinator.com/item?id=49276717</link><guid isPermaLink="false">urn:hackerpapers:submission:1103.0398:49276717</guid><pubDate>Wed, 12 Aug 2026 18:31:31 GMT</pubDate><description>&lt;p&gt;Natural Language Processing Almost from Scratch&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1103.0398/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Natural Language Processing (almost) from Scratch — HN submission</title><link>https://news.ycombinator.com/item?id=14950257</link><guid isPermaLink="false">urn:hackerpapers:submission:1103.0398:14950257</guid><pubDate>Mon, 07 Aug 2017 19:03:23 GMT</pubDate><description>&lt;p&gt;Natural Language Processing (almost) from Scratch&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1103.0398/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Natural Language Processing (almost) from Scratch — mentioned by kyrre</title><link>https://news.ycombinator.com/item?id=13686101</link><guid isPermaLink="false">urn:hackerpapers:mention:1103.0398:13686101</guid><pubDate>Mon, 20 Feb 2017 10:23:27 GMT</pubDate><description>&lt;p&gt;no point wasting your time on nltk: cs224d (videos, lecture notes, assignments) a similar course: https://github.com/oxford-cs-deepnlp-2017/lectures good paper: https://arxiv.org/abs/1103.0398 &amp;quot;Natural Language Processing (almost) from Scratch&amp;quot;&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1103.0398/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Natural Language Processing (almost) from Scratch — mentioned by syllogism</title><link>https://news.ycombinator.com/item?id=10613422</link><guid isPermaLink="false">urn:hackerpapers:mention:1103.0398:10613422</guid><pubDate>Mon, 23 Nov 2015 08:24:55 GMT</pubDate><description>&lt;p&gt;Like a lot of work in NLP at the moment, this is a reasonably straight-forward mash-up of existing techniques. This particular idea is pretty obvious. What wasn&amp;#x27;t obvious was whether it would work well, which was why nobody else got around to trying it yet. The experiments are nicely conducted, with strong baselines across multiple evaluations. The authors also include experiments with variations of the idea, to further validate the approach. To understand the technique, first understand word2vec: http://rare-technologies.com/word2vec-tutorial/…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1103.0398/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Natural Language Processing (almost) from Scratch — HN submission</title><link>https://news.ycombinator.com/item?id=10357863</link><guid isPermaLink="false">urn:hackerpapers:submission:1103.0398:10357863</guid><pubDate>Fri, 09 Oct 2015 02:47:46 GMT</pubDate><description>&lt;p&gt;Natural Language Processing (almost) from Scratch&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1103.0398/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
