<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Research Methods on Po-Wei Chen, MD — Physiatrist &amp; Builder</title><link>https://drpwchen.com/en/categories/research-methods/</link><description>Recent content in Research Methods on Po-Wei Chen, MD — Physiatrist &amp; Builder</description><image><title>Po-Wei Chen, MD — Physiatrist &amp; Builder</title><url>https://drpwchen.com/og-default.png</url><link>https://drpwchen.com/og-default.png</link></image><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 14 Jul 2026 21:40:00 +0800</lastBuildDate><atom:link href="https://drpwchen.com/en/categories/research-methods/index.xml" rel="self" type="application/rss+xml"/><item><title>The last piece of The Paper Trilogy: paper-fetch. Give it a DOI, and it fetches the full text itself</title><link>https://drpwchen.com/en/posts/paper-fetch/</link><pubDate>Tue, 14 Jul 2026 08:15:00 +0800</pubDate><guid>https://drpwchen.com/en/posts/paper-fetch/</guid><description>To let AI read papers for you, you first need the full text. And what usually gets you stuck isn&amp;#39;t the AI—it&amp;#39;s permissions, publishers, and the library. paper-fetch uses a step-by-step route from open access, to official publisher APIs, to your own hospital library to turn a DOI into a full-text PDF, without taking any piracy routes.</description></item><item><title>My data, my benchmark: Swapping the speech recognition (ASR) engine for my lecture note system</title><link>https://drpwchen.com/en/posts/my-data-my-benchmark/</link><pubDate>Mon, 13 Jul 2026 16:31:00 +0800</pubDate><guid>https://drpwchen.com/en/posts/my-data-my-benchmark/</guid><description>MediaTek&amp;#39;s official benchmark already proves Breeze-ASR-25 beats Whisper, but it isn&amp;#39;t testing your task. Using a 180,000-word glossary built from hundreds of textbooks as a yardstick, I found it captures 49% more real vocabulary and runs faster. Another finding not in any model card: the time alignment of the Taiwanese version, Breeze-ASR-26, has regressed. Default decoding only segments once every 30 seconds, which outright breaks when making subtitles or aligning with slides, but enabling word-level timestamps saves it. The testing method is open-sourced.</description></item><item><title>Adding graph retrieval to my medical LLM Wiki, and it actually works this time</title><link>https://drpwchen.com/en/posts/vault-graph-rag/</link><pubDate>Mon, 22 Jun 2026 15:00:00 +0800</pubDate><guid>https://drpwchen.com/en/posts/vault-graph-rag/</guid><description>I threw a new paper on SQL-RAG at Claude to verify it myself: useless for a redundant textbook library, but a great fit for finding &amp;#34;related notes&amp;#34; in a sparse Obsidian medical note vault. After swapping the ranking to personalized PageRank, the proportion of correctly finding related notes jumped from 34% to 84%, and I put it straight into production.</description></item></channel></rss>