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Lyle Ungar

University of Pennsylvania

Social Media Reveals Urban-Rural Differences in Stress across China


Nov 03, 2021
Jesse Cui, Tingdan Zhang, Kokil Jaidka, Dandan Pang, Garrick Sherman, Vinit Jakhetiya, Lyle Ungar, Sharath Chandra Guntuku

* Accepted at AAAI Conference on Web and Social Media (ICWSM) 2022 

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Does BERT Learn as Humans Perceive? Understanding Linguistic Styles through Lexica


Sep 06, 2021
Shirley Anugrah Hayati, Dongyeop Kang, Lyle Ungar

* Accepted at EMNLP 2021 Main Conference 

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Toward Micro-Dialect Identification in Diaglossic and Code-Switched Environments


Oct 10, 2020
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany, Lyle Ungar

* Accepted in EMNLP 2020 

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Generalized SHAP: Generating multiple types of explanations in machine learning


Jun 15, 2020
Dillon Bowen, Lyle Ungar

* 12 pages, 7 figures. Based on a submission to NeurIPS 2020. Dillon Bowen is credited with the original concept, code, data analysis, and initial paper draft. Lyle Ungar is credited with contributions to the draft and mathematical notation. Documentation can be found at https://dsbowen.github.io/gshap/ 

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Learning Word Ratings for Empathy and Distress from Document-Level User Responses


Dec 02, 2019
João Sedoc, Sven Buechel, Yehonathan Nachmany, Anneke Buffone, Lyle Ungar


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Correcting Sociodemographic Selection Biases for Accurate Population Prediction from Social Media


Nov 10, 2019
Salvatore Giorgi, Veronica Lynn, Sandra Matz, Lyle Ungar, H. Andrew Schwartz


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Sentence-Level BERT and Multi-Task Learning of Age and Gender in Social Media


Nov 02, 2019
Muhammad Abdul-Mageed, Chiyu Zhang, Arun Rajendran, AbdelRahim Elmadany, Michael Przystupa, Lyle Ungar


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DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect


Oct 31, 2019
Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany, Arun Rajendran, Lyle Ungar


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Conceptor Debiasing of Word Representations Evaluated on WEAT


Jun 14, 2019
Saket Karve, Lyle Ungar, João Sedoc


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Continual Learning for Sentence Representations Using Conceptors


Apr 18, 2019
Tianlin Liu, Lyle Ungar, João Sedoc

* Accepted by NAACL-2019 

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Unsupervised Post-processing of Word Vectors via Conceptor Negation


Dec 02, 2018
Tianlin Liu, Lyle Ungar, João Sedoc

* Accepted by AAAI-2019 

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Understanding and Measuring Psychological Stress using Social Media


Nov 19, 2018
Sharath Chandra Guntuku, Anneke Buffone, Kokil Jaidka, Johannes Eichstaedt, Lyle Ungar

* Accepted for publication in the proceedings of ICWSM 2019 

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Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors


Nov 17, 2018
Tianlin Liu, João Sedoc, Lyle Ungar

* Accepted by the BioCreative/OHNLP workshop of ACM-BCB 2018 

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Learning Neural Emotion Analysis from 100 Observations: The Surprising Effectiveness of Pre-Trained Word Representations


Oct 25, 2018
Sven Buechel, João Sedoc, H. Andrew Schwartz, Lyle Ungar


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Modeling Empathy and Distress in Reaction to News Stories


Aug 30, 2018
Sven Buechel, Anneke Buffone, Barry Slaff, Lyle Ungar, João Sedoc

* To appear at EMNLP 2018 

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Domain Aware Neural Dialog System


Aug 02, 2017
Sajal Choudhary, Prerna Srivastava, Lyle Ungar, João Sedoc


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Enterprise to Computer: Star Trek chatbot


Aug 02, 2017
Grishma Jena, Mansi Vashisht, Abheek Basu, Lyle Ungar, João Sedoc


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Deriving Verb Predicates By Clustering Verbs with Arguments


Aug 01, 2017
Joao Sedoc, Derry Wijaya, Masoud Rouhizadeh, Andy Schwartz, Lyle Ungar


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Latent Human Traits in the Language of Social Media: An Open-Vocabulary Approach


May 22, 2017
Vivek Kulkarni, Margaret L. Kern, David Stillwell, Michal Kosinski, Sandra Matz, Lyle Ungar, Steven Skiena, H. Andrew Schwartz

* In submission to PLOS One 

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Semantic Word Clusters Using Signed Normalized Graph Cuts


Jan 20, 2016
João Sedoc, Jean Gallier, Lyle Ungar, Dean Foster


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Two Step CCA: A new spectral method for estimating vector models of words


Jun 27, 2012
Paramveer Dhillon, Jordan Rodu, Dean Foster, Lyle Ungar

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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Transfer Learning Using Feature Selection


May 25, 2009
Paramveer S. Dhillon, Dean Foster, Lyle Ungar

* Masters' Thesis 

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