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Found 8 papers, 1 papers with code
Team “NoConflict” at CASE 2021 Task 1: Pretraining for Sentence-Level Protest Event Detection
An ever-increasing amount of text, in the form of social media posts and news articles, gives rise to new challenges and opportunities for the automatic extraction of socio-political events.
Discovering Black Lives Matter Events in the United States: Shared Task 3, CASE 2021
Evaluating the state-of-the-art event detection systems on determining spatio-temporal distribution of the events on the ground is performed unfrequently.
Can Language Models Recognize Convincing Arguments?
The remarkable and ever-increasing capabilities of Large Language Models (LLMs) have raised concerns about their potential misuse for creating personalized, convincing misinformation and propaganda.
Quantifying the Persona Effect in LLM Simulations
However, when the utility of persona variables is low (i. e., explaining <10\% of human annotations), persona prompting has little effect.
Generative Language Models Exhibit Social Identity Biases
In this study, we investigate whether ingroup solidarity and outgroup hostility, fundamental social biases known from social science, are present in 51 large language models.
The Causal News Corpus: Annotating Causal Relations in Event Sentences from News
Leveraging each of these external datasets for training, we achieved up to approximately 64% F1 on the CNC test set without additional fine-tuning.
Drug Re-positioning via Text Augmented Knowledge Graph Embeddings
Drug re-positioning, modeled as a link prediction problem over medical knowledge graphs (KG), has great potential in finding new usage or targets for approved medicine with relatively low cost.
The Multimodal Driver Monitoring Database: A Naturalistic Corpus to Study Driver Attention
We use the Fi- Cap device that continuously tracks the head movement of the driver using fiducial markers, providing frame-based annotations to train head pose algorithms in naturalistic driving conditions.
