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Found 37 papers, 17 papers with code
Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns
We further show that CDA remains effective in low-resource settings, in which a limited set of debiasing documents is used.
What's Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs
We introduce a dataset with utterance pairs from NPR and CNN news interviews annotated for context-dependent paraphrases.
PATCH -- Psychometrics-AssisTed benCHmarking of Large Language Models: A Case Study of Mathematics Proficiency
Third, we release 4 datasets to support measuring and comparing LLM proficiency in grade school mathematics and science against human populations.
Designing and Evaluating General-Purpose User Representations Based on Behavioral Logs from a Measurement Process Perspective: A Case Study with Snapchat
Using this new framework, we design a Transformer-based user model that can produce high-quality general-purpose user representations for instant messaging platforms like Snapchat.
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
Dataset cartography is a simple yet effective dual-model approach that improves the robustness of fine-tuned PLMs.
Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions
We describe our experiments for SemEval-2023 Task 4 on the identification of human values behind arguments (ValueEval).
Measuring the Instability of Fine-Tuning
Fine-tuning pre-trained language models on downstream tasks with varying random seeds has been shown to be unstable, especially on small datasets.
Template-based Abstractive Microblog Opinion Summarisation
We introduce the task of microblog opinion summarisation (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain.
Same Author or Just Same Topic? Towards Content-Independent Style Representations
Linguistic style is an integral component of language.
Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions
Our results thus highlight the necessity to examine the construct validity of text embeddings before deploying them in social science research.
Understanding Public Opinion on Using Hydroxychloroquine for COVID-19 Treatment via Social Media
This paper studies the reactions of social network users on the recommendation of using HCQ for COVID-19 treatment by analyzing the reaction patterns and sentiment of the tweets.
Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework
Style is an integral part of natural language.
Assessing the Reliability of Word Embedding Gender Bias Measures
In this paper, we assess three types of reliability of word embedding gender bias measures, namely test-retest reliability, inter-rater consistency and internal consistency.
On learning and representing social meaning in NLP: a sociolinguistic perspective
The field of NLP has made substantial progress in building meaning representations.
Introducing CAD: the Contextual Abuse Dataset
Online abuse can inflict harm on users and communities, making online spaces unsafe and toxic.
Semantic Journeys: Quantifying Change in Emoji Meaning from 2012-2018
The semantics of emoji has, to date, been considered from a static perspective.
HateCheck: Functional Tests for Hate Speech Detection Models
Detecting online hate is a difficult task that even state-of-the-art models struggle with.
Do Word Embeddings Capture Spelling Variation?
Analyses of word embeddings have primarily focused on semantic and syntactic properties.
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification
Question paraphrase identification is a key task in Community Question Answering (CQA) to determine if an incoming question has been previously asked.
tBERT: Topic Models and BERT Joining Forces for Semantic Similarity Detection
Semantic similarity detection is a fundamental task in natural language understanding.
Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings
Word embeddings are increasingly used for the automatic detection of semantic change; yet, a robust evaluation and systematic comparison of the choices involved has been lacking.
Challenges and frontiers in abusive content detection
Online abusive content detection is an inherently difficult task.
How we do things with words: Analyzing text as social and cultural data
Second, we hope to provide a set of best practices for working with thick social and cultural concepts.
Aiming beyond the Obvious: Identifying Non-Obvious Cases in Semantic Similarity Datasets
Existing datasets for scoring text pairs in terms of semantic similarity contain instances whose resolution differs according to the degree of difficulty.
Comparing Automatic and Human Evaluation of Local Explanations for Text Classification
Text classification models are becoming increasingly complex and opaque, however for many applications it is essential that the models are interpretable.
Emo, Love, and God: Making Sense of Urban Dictionary, a Crowd-Sourced Online Dictionary
On the one hand, the promise of the "wisdom of the crowd" has inspired successful projects such as Wikipedia, which has become the primary source of crowd-based information in many languages.
A Kernel Independence Test for Geographical Language Variation
Quantifying the degree of spatial dependence for linguistic variables is a key task for analyzing dialectal variation.
Computational Sociolinguistics: A Survey
Language is a social phenomenon and variation is inherent to its social nature.
