Dropbox, Inc.

Walter Somerville

Sang Tian

Brian Oh

Jennifer Wong

Danilo Callejas

Devin Mancuso

Jason Stakelon

Richard Chan

Jason Perez

Fiona Rolander

Matthew Safian

Display screen or portion thereof with graphical user interface

The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating a content stack utilizing one or more machine-learning models. In some implementations, the disclosed systems generate and provide, to a user account, a content stack that includes content items corresponding to a topic prompt for the user account. For instance, in some implementations, the disclosed systems utilize content-based signals and account-based signals to generate an account-specific stack formulation graph that represents a plurality of content items and relationships of the content items with each other and with the user account. Additionally, in some implementations, the disclosed systems analyze the account-specific stack formulation graph to generate a content stack from the plurality of content items, the content stack comprising a set of content items corresponding to the topic prompt.

Generating and providing content stacks utilizing machine-learning models

A collaborative content management system is disclosed herein for receiving a command to add an annotation object following a character input into a line of a collaborative content item. The system inserts an annotation object onto the line following the character, detects a selection of the annotation object, and displays a secondary collaborative content item in visual association with the character. The system detects textual content that corresponds to a citation within the secondary collaborative content item, and responsive to detecting the textual content, generates for display a template for inputting fields of a citation. The system receives text entered into one or more of the fields, generates a citation based on the text, and inputs the citation into the secondary collaborative content item.

Collaborative in-line content item annotations

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San Francisco, CA, United States of America

Walter Somerville