Papers
What Did You Think Would Happen? Explaining Agent Behaviour through Intended Outcomes
Herman Yau, Chris Russell, Simon Hadfield
Active Learning Helps Pretrained Models Learn the Intended Task
Alex Tamkin, Dat Nguyen, Salil Deshpande et al.
Exploring Author Context for Detecting Intended vs Perceived Sarcasm
Silviu Oprea, Walid Magdy
iSarcasm: A Dataset of Intended Sarcasm
Silviu Oprea, Walid Magdy
Do Regularization Methods for Shortcut Mitigation Work As Intended?
Haoyang Hong, Ioanna Papanikolaou, Sonali Parbhoo
Efficient Dialogue Strategy to Find Users’ Intended Items from Information Query Results
Kazunori Komatani, Tatsuya Kawahara, Ryosuke Ito et al.
Perceived and Intended Sarcasm Detection with Graph Attention Networks
Joan Plepi, Lucie Flek
The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who
Michael Schlichtkrull, Nedjma Ousidhoum, Andreas Vlachos
Intended Target Identification for Anomia Patients with Gradient-based Selective Augmentation
Jongho Kim, Romain Storaï, Seung-won Hwang
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance
Pedro Henrique Luz de Araujo, Paul Röttger, Dirk Hovy et al.
Erasing More Than Intended? How Concept Erasure Degrades the Generation of Non-Target Concepts
Ibtihel Amara, Ahmed Imtiaz Humayun, Ivana Kajic et al.
Development of Emotion Rankers Based on Intended and Perceived Emotion Labels
Zhenghao Jin, Houwei Cao
Streaming Intended Query Detection using E2E Modeling for Continued Conversation
Shuo-Yiin Chang, Guru Prakash, Zelin Wu et al.
BoFire: Bayesian Optimization Framework Intended for Real Experiments
Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte et al.
SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic
Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson et al.
PALI-NLP at SemEval-2022 Task 6: iSarcasmEval- Fine-tuning the Pre-trained Model for Detecting Intended Sarcasm
Xiyang Du, Dou Hu, Jin Zhi et al.
Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling
Aparna K Ajayan, Krishna Mohanan, Anugraha S et al.
High Tech team at SemEval-2022 Task 6: Intended Sarcasm Detection for Arabic texts
Hamza Alami, Abdessamad Benlahbib, Ahmed Alami
CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic
Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar et al.
TechSSN at SemEval-2022 Task 6: Intended Sarcasm Detection using Transformer Models
Rajalakshmi Sivanaiah, Angel Deborah S, Sakaya Milton R et al.
I2C at SemEval-2022 Task 6: Intended Sarcasm in English using Deep Learning Techniques
Adrián Moreno Monterde, Laura Vázquez Ramos, Jacinto Mata et al.
NULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep Learning
Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy et al.
UoR-NCL at SemEval-2022 Task 6: Using ensemble loss with BERT for intended sarcasm detection
Emmanuel Osei-Brefo, Huizhi Liang
I2C at SemEval-2022 Task 6: Intended Sarcasm Detection on Social Networks with Deep Learning
Pablo Gonzalez Diaz, Pablo Cordon, Jacinto Mata et al.