Tag: 2022
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Capstone Projects 2022
NLP students collaborated with industry mentors from IBM, Interactions, LinkedIn, and Google to develop and implement a variety of Capstone projects to address real-world NLP challenges. The workshop also featured a keynote address about the future of NLP from Professor Ian Lane as well as the annual NLP Industry Panel where leading scientists shared their insights on…
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Comparing Dictionaries and Word Embeddings
Student Team: Anuroop John Abraham, Archit Bose, Kartik, and Utkarsh Garg Project Mentor: Ashvini Jindal, LinkedIn, Dr. Ananth Sankar, LinkedIn An extensive amount of NLP research focuses on learning word representations that accurately reflect their semantic properties. We investigate whether these word embeddings capture the same semantics of the word as its dictionary definition/gloss. To accomplish this, we leverage a reverse…
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MultiModal Knowledge Extraction and Question Answering in Farming
Student Team: Brian Mak, Ignacy Tymoteusz Debicki, Juan Sebastian Reyes, and Sriram Mahesh Project Mentor: Professor Yi Zhang (UCSC), Dr. Yueqi Li (X) and Dr. Kezhen Chen (X) We propose a novel visual long-form question answering system for the farming domain, an area of research with no previous baselines or significant work. We scrape and…
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Neural Models of Supertagging for Semantic Role Labeling and Beyond
Student Team: Anusha Gouravaram, Diji Yang, and Julian Jakob Cremer Project Mentor: Dr. John Chen, Interactions Recent Transformer-type deep neural network models have shown great success in a variety of NLP tasks such as sequence labeling. One sequence tagging task for which work in Transformers is absent is supertagging, which we investigate here. Supertagging, as…
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Probing of Language Models for Code: Exploring Code Style Transfer with Neural Networks
Student team: Anish Kishor Savla, Chih-Kai Ting, Karl Shen Munson, and Serenity Wade Project Mentors: Kiran Kate, IBM Research, Dr. Kavitha Srinivas, IBM Research Style is a significant component of natural language text, able to change the tone of text while keeping the underlying information the same. Even though programming languages have strict rules on…