Are you tired of drowning in a sea of resumes and losing top talent in the hiring whirlwind? Transform your hiring process through a different lens and learn about AI in the Workplace and the Applicant Tracking System (ATS). Whether you're a recent graduate seeking your first job or an undergraduate student looking to delve into more career-oriented opportunities, this workshop by SBU Career Center is designed to equip you with the knowledge and strategies needed to succeed.

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To truly understand human language, we must look at words in the context of the human generating the language. Factors such as demographics, personality, modes of communication, and emotional states have shown to play a crucial role in NLP models pre-LLMs era. Steps of mathematically defining the inclusion of human context in language modeling and more will be discussed with Nikita Soni, a PhD student at Stony Brook University co-advised by H. Andrew Schwartz and Niranjan Balasubramanian. She is the lead organizer of the workshop on human-centered large language modeling.

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The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2025 will be held from June 11th to June 15th, 2025, at the Music City Center, Nashville, TN. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers. Register here.
The Center of Excellence in Wireless and Information Technology (CEWIT) will host the 16th International Conference on Emerging Technologies for a Smarter World (CEWIT2020) virtually on November 5, 2020. The conference will center on the four major fields which are penetrating our business and personal lives: Machine Learning, Artificial Intelligence, Blockchain and Computational Medicine. For more info visit: https://www.cewit.org/.
University Libraries Present: Qualitative data can be challenging to analyze and interpret effectively. In this workshop, SBU Libraries' Data Literacies Lead, Ahmad Pratama will show you how to extract meaningful insights from textual data, including understanding sentiment trends. Learn to explore qualitative data with Python using word clouds, basic natural language processing (NLP) techniques, and lexicon-based sentiment analysis with VADER.
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This session brings together the scientists, agencies, and community partners generating environmental data across New York City to confront a shared challenge: critical atmospheric and marine data is being collected across the region, but too often in silos that limit its reach and impact.

​The program uses Governors Island's own environmental sensing efforts as a working case study, then opens into a broader conversation about how disparate data streams across NYC can be coordinated, shared, and activated--pointing toward the kind of cross-sector collaboration The Exchange's campus is designed to enable.

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The Association for Computational Linguistics is the international scientific and professional society for people working on problems involving natural language and computation. Membership includes the ACL quarterly journals, Computational Linguistics and Transactions of the ACL, reduced registration at most ACL-sponsored conferences, discounts on ACL-sponsored publications, and participation in ACL Special Interest Groups.

An annual meeting is held each summer in locations where significant computational linguistics research is carried out.

For more information and registration, visit the official website.

Topic: AI Seminar: Owen Rambow
Time: Mar 17, 2021 10:00 AM Eastern Time (US and Canada)
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https://stonybrook.zoom.us/j/93614644178?pwd=MzJtVDJYYmU5T1dtMzJiUFMxb0x4dz09
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Natural Language Understanding and Semantic Parsing

(Partly joint work with former colleagues at Elemental Cognition)

Semantic parsing refers to the task of determining the propositional content of language: who did what to whom.  It is part of the larger task of natural language understanding (NLU).  I will start out by discussing what full NLU means, and argue that we are still far away, as a field, from solving full NLU, or even from knowing how to evaluate it.

In the second part of the talk, I will situate semantic parsing in the context of several other NLU subtasks.  Typically, the target representation of semantic parsing uses an ontology (such as PropBank or FrameNet).  Semantic parsing includes the subtasks of word sense disambiguation, argument detection, and argument role labeling.  I will discuss choices among possible target ontologies.  I will justify why we created a new ontology, Hector, based on FrameNet and the lexical resource NOAD, and explain some of its characteristics.

In the third part of the talk, I will present experiments we performed using transformer models.  We obtain best results using a two-phase model, in which we first choose the frame, and then, given the frame, choose the arguments.  We encode the problem for both tasks using indices in the sentence.  While we develop the parser for our new ontology Hector, this approach also beats the state of the art for FrameNet and PropBank parsing.Biography:  I am a professor in the Department of Linguistics at Stony Brook University with a joint appointment in IACS.

Until recently, I was a research scientist at Elemental Cognition. Elemental Cognition is working on deep natural language understanding.

I got my PhD with Aravind Joshi at the University of Pennsylvania in 1994. I have worked at CoGenTex, and at AT&T Labs -- Research, and for many years I was a research scientist at Columbia University in the Center for Computational Learning Systems.