Adobe, Inc.

Sreekanth Reddy

Niranjan Shivanand Kumbi

Balaji Vasan Srinivasan

Niyati Himanshu Chhaya

Viswanathan Swaminathan

Saayan Mitra

Ritwik Sinha

Xiang Chen

Ajay Awatramani

Navita Goyal

Akangsha Sunil Bedmutha

Udit Kalani

Yifu Zheng

Alan Lai

Ayush Agarwal

Roodram Paneri

In some embodiments, techniques for identifying email events generated by bot activity are provided. For example, a process may involve applying bot detection patterns to identify bot activity among email response events.

Bot activity detection for email tracking

Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item is generated. An additional content item that includes additional stage-transition content is identified. A sequencing function outcome indicating a portion of the ratio of interactions is determined. A transition probability of receiving an interaction with stage-transition content and an additional interaction with the additional stage-transition content is calculated. A content provider system is caused to provide a recipient device with interactive content that includes the additional content item.

Machine-learning techniques applied to interaction data for determining sequential content and facilitating interactions in online environments

A content generator system receives a request to generate content for a target entity, and one or more keywords. The content generator system retrieves, for the target entity, a current stage identifier linking the target entity to a current stage within a multi-stage objective. The content generator system generates an input vector including the current stage identifier, a target stage identifier, a token embedding comprising the one or more keywords, and a position embedding for each of the one or more keywords, the target stage identifier associated with a target stage within the multi-stage objective different from the current stage. The content generator system generates output text content for the target entity by applying a generative transformer network to the input vector. The content generator system transmits the output text content to a computing device associated with the target entity.

Content augmentation with machine generated content to meet content gaps during interaction with target entities

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Andhra Pradesh, India

Sreekanth Reddy