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Found 20 papers, 9 papers with code
Measuring Alignment to Authoritarian State Media as Framing Bias
We introduce what is to the best of our knowledge a new task in natural language processing: measuring alignment to authoritarian state media.
ELECTRA is a Zero-Shot Learner, Too
Numerically, compared to MLM-RoBERTa-large and MLM-BERT-large, our RTD-ELECTRA-large has an average of about 8. 4% and 13. 7% improvement on all 15 tasks.
True or False: Does the Deep Learning Model Learn to Detect Rumors?
It is difficult for humans to distinguish the true and false of rumors, but current deep learning models can surpass humans and achieve excellent accuracy on many rumor datasets.
HAT4RD: Hierarchical Adversarial Training for Rumor Detection on Social Media
As such, the robustness and generalization of the current rumor detection model are put into question.
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks
We compare the proposed method with other adversarial training methods and regularization methods, and our method achieves state-of-the-art on all datasets.
Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative Filtering
Our explainability study demonstrates the superiority of and preference for summary-level explanations over other explanation types.
BERT-Based Neural Collaborative Filtering and Fixed-Length Contiguous Tokens Explanation
First is their utilization of traditional word embeddings that could influence prediction performance due to their inability to model the word semantics{'} dynamic characteristic.
Exploiting Microblog Conversation Structures to Detect Rumors
Twitter users communicate by replying to other users{'} messages, forming a conversation structure.
Rumor Detection on Twitter Using Multiloss Hierarchical BiLSTM with an Attenuation Factor
Inspired by the hierarchical model and multitask learning, a multiloss hierarchical BiLSTM model with an attenuation factor is proposed in this paper.
Detecting Argumentative Discourse Acts with Linguistic Alignment
We report the results of preliminary investigations into the relationship between linguistic alignment and dialogical argumentation at the level of discourse acts.
Fill the GAP: Exploiting BERT for Pronoun Resolution
In this paper, we describe our entry in the gendered pronoun resolution competition which achieved fourth place without data augmentation.
Fake News Detection as Natural Language Inference
The remainder of test cases are classified by our ensemble.
Ranked #1 on
Concept-To-Text Generation
on COCO Captions
Probing Neural Network Comprehension of Natural Language Arguments
We are surprised to find that BERT's peak performance of 77% on the Argument Reasoning Comprehension Task reaches just three points below the average untrained human baseline.
SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment
Ethereum is gaining a significant popularity in blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contracts and decentralized applications (Dapps).
NLITrans at SemEval-2018 Task 12: Transfer of Semantic Knowledge for Argument Comprehension
Encoder transfer yields a significant gain to our best model over random initialization.
IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification
This paper describes our approach for SemEval-2017 Task 8.
R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections
The color image is input to the convolutional neural network for automatic feature extraction and training.
