https://hackerpaper.kaipfister.de/p/2309.10814/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=37585532urn:hackerpapers:mention:2309.10814:37585532Wed, 20 Sep 2023 15:35:48 GMT<p>The paper introduces improved performance by prompting LLMs with &quot;natural language embedded programs (NLEP)&quot;. No task-specific prompt is needed. Paper: https://arxiv.org/abs/2309.10814 An automatic NLEP generation toolkit is opensourced: https://github.com/luohongyin/langcode Example Colab notebook is included in the Github repo. This work introduces the following features of NLEP 1. NLEP is a full python program that prints the target response of LLMs. 2. Task-general NLEP prompting outperforms task-specific chain-of-thought prompting on math, symbolic, and natural language. 3. Enable the…</p><p><a href="https://hackerpaper.kaipfister.de/p/2309.10814/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CLhttps://news.ycombinator.com/item?id=37585531urn:hackerpapers:submission:2309.10814:37585531Wed, 20 Sep 2023 15:35:47 GMT<p>Program generation is all you need? For math, symbolic, natural language, etc.</p><p></p><p>1 point; 1 discussion reply on HN. <a href="https://hackerpaper.kaipfister.de/p/2309.10814/">Paper and source history</a>. A submission is not an endorsement.</p>cs.CL