Abu Dhabi
EMNLP 2022
December 7 - 11, 2022
Abu Dhabi, UAE

Overview

Empirical Methods in Natural Language Processing is a leading conference in the area of natural language processing and artificial intelligence. This year, Amazon has more than 40 papers at EMNLP, covering familiar topics like natural-language understanding and question answering, as well as disparate subjects such as as robotics and geospatial learning.

Amazon organizing committee members

Accepted publications

Workshops

EMNLP 2022 Workshop on Ever Evolving NLP
December 7
EvoNLP, the First Workshop on Ever Evolving NLP, a forum to discuss the challenges posed by the dynamic nature of language in the specific context of the current NLP paradigm, dominated by language models.

Website: https://sites.google.com/view/evonlp
EMNLP 2022 Workshop on Massively Multilingual NLU
December 7
The vision of this workshop is to help propel natural language understanding technology into the 50-language, 100-language, and even the 1,000-language regime, both for production systems and for research endeavors. Learn more in our blog post.

Amazon speakers: Dilek Hakkani-Tür

Amazon organizers: Jack FitzGerald, Kay Rottmann, Charith Peris, Christopher Hench

Website: https://mmnlu-22.github.io
EMNLP 2022 Seventh Conference on Machine Translation (WMT22)
December 7 - December 8
Several EASIER partners are involved in the organization of this academic conference, which builds on a series of annual workshops and conferences on statistical machine translation, going back to 2006. This year, for the first time, a shared tasks on SL machine translation (WMT-SLT 22) will be organized.
EMNLP 2022 Workshop on Generation, Evaluation & Metrics (GEM)
December 7 - December 11
EMNLP 2022 Workshop on Natural Legal Language Processing
December 8
The NLLP community aims to bring together researchers and practitioners from Natural Language Processing (NLP) and the legal domain who work on methods and applications of Natural Language Processing by focusing on legal text and text with legal significance.

Website: https://nllpw.org/workshop
EMNLP 2022 Workshop on Multilingual Representation Learning
December 8
This workshop aims to bring together the research community consisting of scientists studying different aspects in multilingual representation learning, currently the most promising approach to improve the NLP in low-resource or underrepresented languages, and provide the rapidly growing number of researchers working on the topic with a means of communication and an opportunity to present their work and exchange ideas.
EMNLP 2022 Workshop on Arabic Natural Language Processing (WANLP)
December 8
EMNLP 2022 Workshop on Novel Ideas in Learning-to-Learn through Interaction (NILLI)
December 8
This interdisciplinary research topic unifies research paradigms of lifelong learning, natural language processing, embodied learning, reinforcement learning, robot learning and multi-modal learning towards building interactive and interpretable AI.

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To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. We are looking for PhD students excited about working on Automated Reasoning or Storage System problems at the intersection of theory and practice to drive innovation and provide value for our customers. AWS Automated Reasoning teams deliver tools that are called billions of times daily. Amazon development teams are integrating automated-reasoning tools such as Dafny, P, and SAW into their development processes, raising the bar on the security, durability, availability, and quality of our products. AWS Automated Reasoning teams are changing how computer systems built on top of the cloud are developed and operated. AWS Automated Reasoning teams work in areas including: Distributed proof search, SAT and SMT solvers, Reasoning about distributed systems, Automating regulatory compliance, Program analysis and synthesis, Security and privacy, Cryptography, Static analysis, Property-based testing, Model-checking, Deductive verification, compilation into mainstream programming languages, Automatic test generation, and Static and dynamic methods for concurrent systems. AWS Storage Systems teams manage trillions of objects in storage, retrieving them with predictable low latency, building software that deploys to thousands of hosts, achieving 99.999999999% (you didn’t read that wrong, that’s 11 nines!) durability. AWS storage services grapple with exciting problems at enormous scale. Amazon S3 powers businesses across the globe that make the lives of customers better every day, and forms the backbone for applications at all scales and in all industries ranging from multimedia to genomics. This scale and data diversity requires constant innovation in algorithms, systems and modeling. AWS Storage Systems teams work in areas including: Error-correcting coding and durability modeling, system and distributed system performance optimization and modeling, designing and implementing distributed, multi-tenant systems, formal verification and strong, practical assurances of correctness, bits-IOPS-Watts: the interplay between computation, performance, and energy, data compression - both general-purpose and domain specific, research challenges with storage media, both existing and emerging, and exploring the intersection between storage and quantum technologies. As an Applied Science Intern, you will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment who is comfortable with ambiguity. Amazon believes that scientific innovation is essential to being the world’s most customer-centric company. Our ability to have impact at scale allows us to attract some of the brightest minds in Automated Reasoning and related fields. Our scientists work backwards to produce innovative solutions that delight our customers. Please visit https://www.amazon.science (https://www.amazon.science/) for more information.
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To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. Help us develop the algorithms and models that power computer vision services at Amazon, such as Amazon Rekognition, Amazon Go, Visual Search, and more! We are combining computer vision, mobile robots, advanced end-of-arm tooling and high-degree of freedom movement to solve real-world problems at huge scale. As an intern, you will help build solutions where visual input helps the customers shop, anticipate technological advances, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. You will own the design and development of end-to-end systems and have the opportunity to write technical white papers, create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Amazon Scientist use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science
US, WA, Seattle
To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. Help us develop the algorithms and models that power computer vision services at Amazon, such as Amazon Rekognition, Amazon Go, Visual Search, and more! We are combining computer vision, mobile robots, advanced end-of-arm tooling and high-degree of freedom movement to solve real-world problems at huge scale. As an intern, you will help build solutions where visual input helps the customers shop, anticipate technological advances, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. You will own the design and development of end-to-end systems and have the opportunity to write technical white papers, create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Amazon Scientist use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science
US, WA, Seattle
To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. Are you a Masters or PhD student interested in machine learning? We are looking for skilled scientists capable of putting Machine Learning theory into practice through experimentation and invention, leveraging machine learning techniques (such as random forest, Bayesian networks, ensemble learning, clustering, etc.), and implementing learning systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.