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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2401.16475/</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/2401.16475/feed.xml" rel="self" type="application/rss+xml" /><item><title>InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification — mentioned by pravj</title><link>https://news.ycombinator.com/item?id=45332062</link><guid isPermaLink="false">urn:hackerpapers:mention:2401.16475:45332062</guid><pubDate>Mon, 22 Sep 2025 11:44:57 GMT</pubDate><description>&lt;p&gt;This resonates a lot with some observations I drafted last week about &amp;quot;AI Slop&amp;quot; at the workplace. Overall, people are making a net-negative contribution by not having a sense of when to review/filter the responses generated by AI tools, because either (i) someone else is required to make that additional effort, or (ii) the problem is not solved properly. This sounds similar to a few patterns I noted - The average length of documents and emails has increased. - Not alarmingly so, but people have started writing Slack/Teams responses with LLMs. (and it’s not just to fix the grammar.) - Many…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2401.16475/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification — HN submission</title><link>https://news.ycombinator.com/item?id=39252249</link><guid isPermaLink="false">urn:hackerpapers:submission:2401.16475:39252249</guid><pubDate>Sun, 04 Feb 2024 17:25:22 GMT</pubDate><description>&lt;p&gt;Characterizing and Recovering Information Loss in Text Simplification&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/2401.16475/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
