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arXiv · 2602.08945

GitSearch: Enhancing Community Notes Generation with Gap-Informed Targeted Search

Sahajpreet Singh·Kokil Jaidka·Min-Yen Kan
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Abstract

Community-based moderation offers a scalable alternative to centralized fact-checking, yet it faces significant structural challenges, and existing AI-based methods fail in "cold start" scenarios. To tackle these challenges, we introduce GitSearch (Gap-Informed Targeted Search), a framework that treats human-perceived quality gaps, such as missing context, etc., as first-class signals. GitSearch has a three-stage pipeline: identifying information deficits, executing real-time targeted web-retrieval to resolve them, and synthesizing platform-compliant notes. To facilitate evaluation, we present PolBench, a benchmark of 78,698 U.S. political tweets with their associated Community Notes. We find GitSearch achieves 99% coverage, almost doubling coverage over the state-of-the-art. GitSearch surpasses human-authored helpful notes with a 69% win rate and superior helpfulness scores (3.87 vs. 3.36), demonstrating retrieval effectiveness that balanced the trade-off between scale and quality.

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Sahajpreet Singh, Kokil Jaidka, Min-Yen Kan. 2026-02-09. GitSearch: Enhancing Community Notes Generation with Gap-Informed Targeted Search. https://arxiv.org/abs/2602.08945

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