1.4k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Southern CaliforniaUS710 papers
- Southern States UniversityUS31 papers
- University of California, BerkeleyUS23 papers
- Carnegie Mellon UniversityUS18 papers
- University of California, Los AngelesUS18 papers
- Princeton UniversityUS17 papers
- Stanford UniversityUS16 papers
- California Institute of TechnologyUS15 papers
- Centre National de la Recherche ScientifiqueFR13 papers
- University of MichiganUS13 papers
- University of Illinois Urbana-ChampaignUS12 papers
- Google (United States)US11 papers
11 papers · 2 filters
Fair Hate Speech Detection through Evaluation of Social Group Counterfactuals
Aida Mostafazadeh Davani, Ali Omrani, Brendan Kennedy +3
Approaches for mitigating bias in supervised models are designed to reduce models' dependence on specific sensitive features of the input data, e.g., mentioned social groups. Howev…
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Mrigank Raman, Aaron Chan, Siddhant Agarwal +7
Knowledge graphs (KGs) have helped neural models improve performance on various knowledge-intensive tasks, like question answering and item recommendation. By using attention over…
Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies
Kung-Hsiang Huang, Nanyun Peng
Fully understanding narratives often requires identifying events in the context of whole documents and modeling the event relations. However, document-level event extraction is a c…
A Variational Approach to Unsupervised Sentiment Analysis
Ziqian Zeng, Wenxuan Zhou, Xin Liu +4
In this paper, we propose a variational approach to unsupervised sentiment analysis. Instead of using ground truth provided by domain experts, we use target-opinion word pairs as a…
An Experimental Study of The Effects of Position Bias on Emotion CauseExtraction
Jiayuan Ding, Mayank Kejriwal
Emotion Cause Extraction (ECE) aims to identify emotion causes from a document after annotating the emotion keywords. Some baselines have been proposed to address this problem, suc…
Contextualizing Hate Speech Classifiers with Post-hoc Explanation
Brendan Kennedy, Xisen Jin, Aida Mostafazadeh Davani +2
Hate speech classifiers trained on imbalanced datasets struggle to determine if group identifiers like "gay" or "black" are used in offensive or prejudiced ways. Such biases manife…
Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
Peifeng Wang, Nanyun Peng, Filip Ilievski +2
Commonsense question answering (QA) requires background knowledge which is not explicitly stated in a given context. Prior works use commonsense knowledge graphs (KGs) to obtain th…
Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models
Bill Yuchen Lin, Seyeon Lee, Rahul Khanna +1
Recent works show that pre-trained language models (PTLMs), such as BERT, possess certain commonsense and factual knowledge. They suggest that it is promising to use PTLMs as "neur…
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation
Dong-Ho Lee, Rahul Khanna, Bill Yuchen Lin +6
Successfully training a deep neural network demands a huge corpus of labeled data. However, each label only provides limited information to learn from and collecting the requisite…
Zero-Shot Learning of Text Adventure Games with Sentence-Level Semantics
Xusen Yin, Jonathan May
Reinforcement learning algorithms such as Q-learning have shown great promise in training models to learn the optimal action to take for a given system state; a goal in application…
Efficient Sentence Embedding via Semantic Subspace Analysis
Bin Wang, Fenxiao Chen, Yuncheng Wang +1
A novel sentence embedding method built upon semantic subspace analysis, called semantic subspace sentence embedding (S3E), is proposed in this work. Given the fact that word embed…