This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Adobe, Inc.. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Chirag Agarwal: Innovator in Vision-Language Models
Introduction
Chirag Agarwal is a notable inventor based in Noida, India. He has made significant contributions to the field of artificial intelligence, particularly in the area of vision-language models. His innovative work focuses on debiasing these models to enhance their performance and reliability.
Latest Patents
Chirag Agarwal holds a patent titled "Debiasing vision-language models with additive residuals." This patent relates to systems, non-transitory computer-readable media, and methods for debiasing vision-language models utilizing additive residual learning. The disclosed systems generate an encoded image representation of a digital image using an image encoder of a vision-language neural network. Furthermore, the systems extract a protected attribute encoding from the encoded image representation, allowing for the determination of a debiased image encoding by combining the protected attribute encoding and the encoded image representation. He has 1 patent to his name.
Career Highlights
Chirag Agarwal is currently employed at Adobe Inc., where he continues to push the boundaries of technology through his research and development efforts. His work at Adobe has allowed him to collaborate with other talented professionals in the field.
Collaborations
Some of his notable coworkers include Mayur Hemani and Ashish Seth, who contribute to the innovative environment at Adobe Inc. Their collective expertise fosters a culture of creativity and advancement in technology.
Conclusion
Chirag Agarwal is a prominent figure in the realm of artificial intelligence, particularly in the development of debiasing techniques for vision-language models. His contributions are paving the way for more equitable and effective AI systems.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
