{"id":40333,"date":"2026-04-11T11:28:28","date_gmt":"2026-04-11T09:28:28","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/dataset-idea-for-training-retrieval-judgment-instead-of-just-retrieval-itself\/"},"modified":"2026-04-11T11:28:28","modified_gmt":"2026-04-11T09:28:28","slug":"dataset-idea-for-training-retrieval-judgment-instead-of-just-retrieval-itself","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/dataset-idea-for-training-retrieval-judgment-instead-of-just-retrieval-itself\/","title":{"rendered":"Dataset Idea For Training Retrieval Judgment Instead Of Just Retrieval Itself"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>Been thinking about a failure mode that feels more like a <strong>dataset problem<\/strong> than a tooling problem:<\/p>\n<p>the retrieval stack is available<br \/> the tool is wired<br \/> the docs are there<\/p>\n<p>but the model still answers from memory on requests that clearly depend on current information.<\/p>\n<p>So the issue is not always \u201cbad search.\u201d<br \/> A lot of the time it is the <strong>trigger decision<\/strong>:<br \/> when should the model actually check, and when should it not?<\/p>\n<p>I\u2019ve been looking at a Lane 07 style setup for this where the supervision signal is explicit:<\/p>\n<ul>\n<li><code>needs_search: true<\/code> when freshness matters<\/li>\n<li><code>needs_search: false<\/code> when model knowledge is enough<\/li>\n<\/ul>\n<p>Example row:<\/p>\n<pre><code>{ \"sample_id\": \"lane_07_search_triggering_en_00000008\", \"needs_search\": true, \"assistant_response\": \"This is best answered with a quick lookup for current data. If you want me to verify it, I can.\" } <\/code><\/pre>\n<p>What I like about this framing is that it does <strong>not<\/strong> just teach \u201cretrieve more.\u201d<br \/> It teaches both sides of the boundary:<\/p>\n<ul>\n<li>when to trigger<\/li>\n<li>when to hold back<\/li>\n<\/ul>\n<p>That seems useful because bad gating hurts in both directions:<\/p>\n<ul>\n<li>over-triggering adds latency and cost<\/li>\n<li>under-triggering gives stale but confident answers<\/li>\n<\/ul>\n<p>I\u2019m experimenting with dataset structures for this kind of retrieval judgment and I think it is an underrated training target compared with just improving retrieval quality itself.<\/p>\n<p>Curious how others here would structure it:<\/p>\n<ul>\n<li>binary <code>needs_search<\/code><\/li>\n<li>richer labels<\/li>\n<li>classifier-style trigger data<\/li>\n<li>conversational SFT rows<\/li>\n<li>hybrid setup<\/li>\n<\/ul>\n<p>Would love to hear if anyone else is working on datasets for this boundary.<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/JayPatel24_\"> \/u\/JayPatel24_ <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1sidn9s\/dataset_idea_for_training_retrieval_judgment\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1sidn9s\/dataset_idea_for_training_retrieval_judgment\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-40333 jlk' href='javascript:void(0)' data-task='like' data-post_id='40333' data-nonce='9941108d62' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-40333 lc'>0<\/span><\/a><\/div><\/div> <div class='status-40333 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>Been thinking about a failure mode that feels more like a dataset problem than a tooling problem:&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-40333","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/40333","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=40333"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/40333\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=40333"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=40333"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=40333"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}