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Found 16 papers, 12 papers with code
Scubed at 3C task A - A simple baseline for citation context purpose classification
We present our team Scubed’s approach in the ‘3C’ Citation Context Classification Task, Subtask A, citation context purpose classification.
Scubed at 3C task B - A simple baseline for citation context influence classification
Our best model on the leaderboard is a random forest classifier using only the citation context text.
PyTAIL: Interactive and Incremental Learning of NLP Models with Human in the Loop for Online Data
For natural language processing (NLP) tasks that utilize a collection of features based on lexicons and rules, it is important to adapt these features to the changing data.
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.
NTULM: Enriching Social Media Text Representations with Non-Textual Units
We refer to these annotations as Non-Textual Units (NTUs).
Robust Candidate Generation for Entity Linking on Short Social Media Texts
Entity Linking (EL) is the gateway into Knowledge Bases.
TweetNERD -- End to End Entity Linking Benchmark for Tweets
Named Entity Recognition and Disambiguation (NERD) systems are foundational for information retrieval, question answering, event detection, and other natural language processing (NLP) applications.
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance.
Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair Prediction
We evaluate a simple approach to improving zero-shot multilingual transfer of mBERT on social media corpus by adding a pretraining task called translation pair prediction (TPP), which predicts whether a pair of cross-lingual texts are a valid translation.
LMSOC: An Approach for Socially Sensitive Pretraining
Although language depends heavily on the geographical, temporal, and other social contexts of the speaker, these elements have not been incorporated into modern transformer-based language models.
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
However, we demonstrate that formalized fairness metrics and quantitative analysis on their own are insufficient for capturing the risk of representational harm in automatic cropping.
Exploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social media
Hate Speech has become a major content moderation issue for online social media platforms.
A Framework for Generating Annotated Social Media Corpora with Demographics, Stance, Civility, and Topicality
In this paper we introduce a framework for annotating a social media text corpora for various categories.
Assessing Demographic Bias in Named Entity Recognition
Named Entity Recognition (NER) is often the first step towards automated Knowledge Base (KB) generation from raw text.
Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
We also investigated the utility of task label marginalization, joint label classification, and joint training on multilingual datasets as possible improvements to our models.
Semi-supervised Named Entity Recognition in noisy-text
In this paper, we report on the solution [ST] we submitted to the WNUT 2016 NER shared task.
