Maria Glenski
9 papers · 2018–2023 · 5 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (31) π Conference Polyglot Β· Silver
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Prolific Year Β· Productive
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Renaissance Researcher
(5)
ποΈ
Keyword Collector
(51)
Venues
Top co-authors
Research topics
Machine Learning
(8)
Artificial Intelligence
(6)
Core AI
(6)
Natural Language Processing
(5)
Application Areas
(4)
Applications
(4)
Learning Types Β· Machine Learning
(4)
Deep Learning
(2)
Interdisciplinary
(2)
Core Methods
(2)
Learning Types Β· Deep Learning
(2)
Linguistics
(2)
Resources & Methods
(2)
Understanding
(2)
Data Science & Analytics
(1)
Keywords
text classification
(4)
deception detection
(4)
language model
(3)
model evaluation
(2)
domain adaptation
(1)
bias detection
(1)
zero-shot learning
(1)
adversarial attack
(1)
domain generalization
(1)
named entity recognition
(1)
multimodal learning
(1)
computational linguistics
(1)
social media analysis
(1)
machine reading comprehension
(1)
contextual representation
(1)
deep learning
(1)
document classification
(1)
semantic similarity
(1)
model robustness
(1)
adversarial robustness
(1)
Papers
Unsupervised Keyphrase Extraction via Interpretable Neural Networks
EACL 2023
Foundation Models of Scientific Knowledge for Chemistry: Opportunities, Challenges and Lessons Learned
ACL 2022
CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation
NAACL 2021
Evaluating Deception Detection Model Robustness To Linguistic Variation
NAACL 2021
Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Community
EMNLP 2021
Improving Synonym Recommendation Using Sentence Context
EMNLP 2021
Leveraging Community and Author Context to Explain the Performance and Bias of Text-Based Deception Detection Models
NAACL 2021
Towards Trustworthy Deception Detection: Benchmarking Model Robustness across Domains, Modalities, and Languages
COLING 2020
Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources
ACL 2018