Natural Language Processing

In Natural Language Processing (NLP), we focus on how computers understand and interact with humans through natural conversation and text. We develop new NLP methods for collecting, processing, analyzing and understanding large amounts of natural language data for diverse applications such as intelligent conversational assistants, natural language search, document intelligence and knowledge acquisition.  

Our research projects span natural language understanding, dialogue systems, document semantics and affect understanding, document re-synthesis, text-mining, structured information extraction, knowledge acquisition and representation, joint language and vision-based understanding of images and videos, deep learning, and the use of natural language for computational creativity.  Our work includes efforts in intelligent assistants, multimodal search, document understanding, content generation, affect modelling, and multimodal content synthesis.  

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Aparna Garimella

Research Scientist

Natwar Modani

Senior Research Manager

Niyati Chhaya

Sr. Research Scientist

View our latest publicationsView More

Dynamic Path Reasoning for Measurement Relation Extraction

Veyseh, A., Dernoncourt, F., Nguyen, T. (Aug. 6, 2021)

SemEval 2021

Unleash GPT-2 Power for Event Detection

Veyseh, A., Lai, V., Dernoncourt, F., Nguyen, T. (Aug. 4, 2021)

ACL 2021

Document-Level Event Argument Extraction via Optimal Transport

Veyseh, A., Van Nguyen, M., Dernoncourt, F., Min, B., Nguyen, T. (Aug. 4, 2021)

ACL 2021

Knowledge Graphs

At Adobe Research, research scientists are exploring new ways of using knowledge graphs to develop tools to inform and inspire our customers. Knowledge graphs represent complex real-world material in a rich, interconnected network, helping users find answers that might otherwise be hidden.

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Join us!

We are looking for researchers, engineers, and interns to take our technologies to the next level. We're recruiting, and we would love to hear from you!