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09/20/2023
Examining the Limitations of Computational Rumor Detection Models Trained on Static Datasets
A crucial aspect of a rumor detection model is its ability to generalize...
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09/15/2023
Frustratingly Simple Memory Efficiency for Pre-trained Language Models via Dynamic Embedding Pruning
The extensive memory footprint of pre-trained language models (PLMs) can...
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09/14/2023
Improving Multimodal Classification of Social Media Posts by Leveraging Image-Text Auxiliary tasks
Effectively leveraging multimodal information from social media posts is...
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09/06/2023
A Multimodal Analysis of Influencer Content on Twitter
Influencer marketing involves a wide range of strategies in which brands...
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05/26/2023
Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues
User Satisfaction Modeling (USM) is one of the popular choices for task-...
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05/23/2023
Navigating Prompt Complexity for Zero-Shot Classification: A Study of Large Language Models in Computational Social Science
Instruction-tuned Large Language Models (LLMs) have exhibited impressive...
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05/23/2023
Active Learning Principles for In-Context Learning with Large Language Models
The remarkable advancements in large language models (LLMs) have signifi...
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05/22/2023
Rethinking Semi-supervised Learning with Language Models
Semi-supervised learning (SSL) is a popular setting aiming to effectivel...
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05/21/2023
On the Limitations of Simulating Active Learning
Active learning (AL) is a human-and-model-in-the-loop paradigm that iter...
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05/18/2023
Trading Syntax Trees for Wordpieces: Target-oriented Opinion Words Extraction with Wordpieces and Aspect Enhancement
State-of-the-art target-oriented opinion word extraction (TOWE) models t...
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05/17/2023
Incorporating Attribution Importance for Improving Faithfulness Metrics
Feature attribution methods (FAs) are popular approaches for providing i...
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02/28/2023
Self-training through Classifier Disagreement for Cross-Domain Opinion Target Extraction
Opinion target extraction (OTE) or aspect extraction (AE) is a fundament...
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02/06/2023
It's about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological Splits
New events emerge over time influencing the topics of rumors in social m...
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10/17/2022
On the Impact of Temporal Concept Drift on Model Explanations
Explanation faithfulness of model predictions in natural language proces...
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10/14/2022
HashFormers: Towards Vocabulary-independent Pre-trained Transformers
Transformer-based pre-trained language models are vocabulary-dependent, ...
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09/18/2022
Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection
State-of-the-art approaches for hate-speech detection usually exhibit po...
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05/06/2022
Combining Humor and Sarcasm for Improving Political Parody Detection
Parody is a figurative device used for mimicking entities for comedic or...
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04/21/2022
Identifying and Characterizing Active Citizens who Refute Misinformation in Social Media
The phenomenon of misinformation spreading in social media has developed...
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04/16/2022
A Hierarchical N-Gram Framework for Zero-Shot Link Prediction
Due to the incompleteness of knowledge graphs (KGs), zero-shot link pred...
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03/23/2022
Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detection
Hate speech classifiers exhibit substantial performance degradation when...
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03/20/2022
How does the pre-training objective affect what large language models learn about linguistic properties?
Several pre-training objectives, such as masked language modeling (MLM),...
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03/11/2022
Automatic Identification and Classification of Bragging in Social Media
Bragging is a speech act employed with the goal of constructing a favora...
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02/28/2022
An Empirical Study on Explanations in Out-of-Domain Settings
Recent work in Natural Language Processing has focused on developing app...
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10/03/2021
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
Law, interpretations of law, legal arguments, agreements, etc. are typic...
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09/08/2021
Active Learning by Acquiring Contrastive Examples
Common acquisition functions for active learning use either uncertainty ...
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09/04/2021
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling
Masked language modeling (MLM), a self-supervised pretraining objective,...
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09/02/2021
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction
Target-oriented opinion words extraction (TOWE) (Fan et al., 2019b) is a...
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09/01/2021
Point-of-Interest Type Prediction using Text and Images
Point-of-interest (POI) type prediction is the task of inferring the typ...
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08/31/2021
Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience
Pretrained transformer-based models such as BERT have demonstrated state...
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08/27/2021
Translation Error Detection as Rationale Extraction
Recent Quality Estimation (QE) models based on multilingual pre-trained ...
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07/01/2021
Knowledge Distillation for Quality Estimation
Quality Estimation (QE) is the task of automatically predicting Machine ...
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05/09/2021
Analyzing Online Political Advertisements
Online political advertising is a central aspect of modern election camp...
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05/06/2021
On the Ethical Limits of Natural Language Processing on Legal Text
Natural language processing (NLP) methods for analyzing legal text offer...
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05/06/2021
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification
Neural network architectures in natural language processing often use at...
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04/16/2021
Bayesian Active Learning with Pretrained Language Models
Active Learning (AL) is a method to iteratively select data for annotati...
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04/16/2021
Variable Instance-Level Explainability for Text Classification
Despite the high accuracy of pretrained transformer networks in text cla...
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03/24/2021
Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases
Interpretability or explainability is an emerging research field in NLP....
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03/23/2021
Modeling the Severity of Complaints in Social Media
The speech act of complaining is used by humans to communicate a negativ...
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10/21/2020
Complaint Identification in Social Media with Transformer Networks
Complaining is a speech act extensively used by humans to communicate a ...
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10/06/2020
LEGAL-BERT: The Muppets straight out of Law School
BERT has achieved impressive performance in several NLP tasks. However, ...
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10/04/2020
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels
Large-scale Multi-label Text Classification (LMTC) has a wide range of N...
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09/30/2020
Point-of-Interest Type Inference from Social Media Text
Physical places help shape how we perceive the experiences we have there...
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05/29/2020
Automatic Generation of Topic Labels
Topic modelling is a popular unsupervised method for identifying the und...
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05/21/2020
Unsupervised Quality Estimation for Neural Machine Translation
Quality Estimation (QE) is an important component in making Machine Tran...
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04/28/2020
Analyzing Political Parody in Social Media
Parody is a figurative device used to imitate an entity for comedic or c...
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06/10/2019
Automatically Identifying Complaints in Social Media
Complaining is a basic speech act regularly used in human and computer m...
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06/05/2019
Neural Legal Judgment Prediction in English
Legal judgment prediction is the task of automatically predicting the ou...
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05/26/2019
Extreme Multi-Label Legal Text Classification: A case study in EU Legislation
We consider the task of Extreme Multi-Label Text Classification (XMTC) i...
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03/29/2019
Re-Ranking Words to Improve Interpretability of Automatically Generated Topics
Topics models, such as LDA, are widely used in Natural Language Processi...
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08/26/2018