---
type: "raw_signal"
id: "castle-training-natural-language-search-before-the-first-06a78f"
slug: "castle-training-natural-language-search-before-the-first-06a78f"
title: "CASTLE: training natural language search before the first real query"
description: "## Airbnb introduces CASTLE for natural-language search cold start"
retrieval_nugget: "## Airbnb introduces CASTLE for natural-language search cold start"
observed_at: "2026-10-13"
record_date: "2026-10-13"
date_kind: "observed_at"
why_it_matters: "The company reports a KL divergence of 1.01 between generated and real query distributions, compared with 9.33 for its best baseline. In a human evaluation of 200 triplets, three subject-matter experts agreed with relevance assignments at rates of 91–93%. For cases without contrastive booking data, including newly listed properties, Airbnb says it supplements the method with an LLM-based Virtual J"
novelty: "notable"
verification_level: "source-linked"
signal_type: "research"
source_platform: "airbnb.tech"
topics: []
entities: ["Airbnb","CASTLE","CIKM 2026"]
related_patterns: []
source_url: "https://airbnb.tech/ai-ml/castle-training-natural-language-search-before-the-first-real-query"
source_urls: ["https://airbnb.tech/ai-ml/castle-training-natural-language-search-before-the-first-real-query"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "signal:castle-training-natural-language-search-before-the-first-06a78f"
status: "published"
visuals: []
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
routes: {"html":"https://newruntime.com/signals/castle-training-natural-language-search-before-the-first-06a78f/","markdown":"https://newruntime.com/signals/castle-training-natural-language-search-before-the-first-06a78f.md","json":"https://newruntime.com/signals/castle-training-natural-language-search-before-the-first-06a78f.json"}
---

# CASTLE: training natural language search before the first real query

## Retrieval answer

## Airbnb introduces CASTLE for natural-language search cold start

## Airbnb introduces CASTLE for natural-language search cold start

Airbnb has described CASTLE (Contrastive And Seed-guided Training for natural Language sEarch), a framework for preparing natural-language search before real user queries are available. It generates synthetic queries and relevance labels together, using contrastive listing pairs derived from de-identified booking sessions selected according to privacy permissions. A booked listing is treated as positive and a viewed-but-not-booked alternative as negative; the generated query is intended to fit the former rather than the latter.

The company reports a KL divergence of 1.01 between generated and real query distributions, compared with 9.33 for its best baseline. In a human evaluation of 200 triplets, three subject-matter experts agreed with relevance assignments at rates of 91–93%. For cases without contrastive booking data, including newly listed properties, Airbnb says it supplements the method with an LLM-based Virtual Judge. These are company-reported results; the article does not establish independent replication.

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

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