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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2310.04948/</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/2310.04948/feed.xml" rel="self" type="application/rss+xml" /><item><title>TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting — mentioned by longdog</title><link>https://news.ycombinator.com/item?id=39824334</link><guid isPermaLink="false">urn:hackerpapers:mention:2310.04948:39824334</guid><pubDate>Tue, 26 Mar 2024 04:45:44 GMT</pubDate><description>&lt;p&gt;Interesting, but I&amp;#x27;m very skeptical. There are over a dozen transformers-based foundation time series model released in the past year and without fail, every one of them claims to be at or near SOTA. For example: - Time-LLM (https://arxiv.org/abs/2310.01728) - Lag-Llama (https://arxiv.org/abs/2310.08278) - UniTime (https://arxiv.org/abs/2310.09751) - TEMPO (https://arxiv.org/abs/2310.04948) - TimeGPT (https://arxiv.org/abs/2310.03589) - TimesFM (https://arxiv.org/html/2310.10688v2) - GPT4TS (https://arxiv.org/pdf/2308.08469.pdf) Yet not a SINGLE transformer-based model I&amp;#x27;ve managed to…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2310.04948/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
