2 citations · 2 across the 3 of their papers we have counts for
4 papers
Community-Driven API and AI Writer Design for Openly Scaling Community Notes
Brad Miller, Jay Baxter, Jiansong Chao +3
Community Notes is a crowd-sourced approach for adding context to posts on X. Contributors propose and rate notes, forming the inputs to an open-source, open-data algorithm that de…
Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking
Nikil Roashan Selvam, Jay Baxter, Sophie Hilgard +4
Crowdsourced fact-checking systems have been adopted by major social media companies such as X, Meta, TikTok and Google with the aim of combating misleading information at scale wi…
Scaling Human Judgment in Community Notes with LLMs
Haiwen Li, Soham De, Manon Revel +6
This paper argues for a new paradigm for Community Notes in the LLM era: an open ecosystem where both humans and LLMs can write notes, and the decision of which notes are helpful e…
Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking
Soham De, Michiel A. Bakker, Jay Baxter +1
X's Community Notes, a crowd-sourced fact-checking system, allows users to annotate potentially misleading posts. Notes rated as helpful by a diverse set of users are prominently d…