Papers
One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
Marco Damonte, Emilio Monti
One Teacher is Enough? Pre-trained Language Model Distillation from Multiple Teachers
Chuhan Wu, Fangzhao Wu, Yongfeng Huang
On Finding the K-best Non-projective Dependency Trees
Ran Zmigrod, Tim Vieira, Ryan Cotterell
On Knowledge Distillation for Translating Erroneous Speech Transcriptions
Ryo Fukuda, Katsuhito Sudoh, Satoshi Nakamura
Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
Vânia Mendonça, Ricardo Rei, Luisa Coheur et al.
On Orthogonality Constraints for Transformers
Aston Zhang, Alvin Chan, Yi Tay et al.
On Positivity Bias in Negative Reviews
Madhusudhan Aithal, Chenhao Tan
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation
Wei Zhang, Ziming Huang, Yada Zhu et al.
On Sparsifying Encoder Outputs in Sequence-to-Sequence Models
Biao Zhang, Ivan Titov, Rico Sennrich
On the Copying Behaviors of Pre-Training for Neural Machine Translation
Xuebo Liu, Longyue Wang, Derek F. Wong et al.
On the Cost-Effectiveness of Stacking of Neural and Non-Neural Methods for Text Classification: Scenarios and Performance Prediction
Christian Gomes, Marcos Goncalves, Leonardo Rocha et al.
On the cross-lingual transferability of multilingual prototypical models across NLU tasks
Oralie Cattan, Sophie Rosset, Christophe Servan
On the differences between BERT and MT encoder spaces and how to address them in translation tasks
Raúl Vázquez, Hande Celikkanat, Mathias Creutz et al.
On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers
Tianchu Ji, Shraddhan Jain, Michael Ferdman et al.
On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation
Ruidan He, Linlin Liu, Hai Ye et al.
On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study
Divyansh Kaushik, Douwe Kiela, Zachary C. Lipton et al.
On the Ethical Limits of Natural Language Processing on Legal Text
Dimitrios Tsarapatsanis, Nikolaos Aletras
On-the-Fly Attention Modulation for Neural Generation
Yue Dong, Chandra Bhagavatula, Ximing Lu et al.
On the Gap between Adoption and Understanding in NLP
Federico Bianchi, Dirk Hovy
On the Generation of Medical Dialogs for COVID-19
Meng Zhou, Zechen Li, Bowen Tan et al.
On the Interaction of Belief Bias and Explanations
Ana Valeria González, Anna Rogers, Anders Søgaard
On the Interplay Between Fine-tuning and Composition in Transformers
Lang Yu, Allyson Ettinger
On the Lack of Robust Interpretability of Neural Text Classifiers
Muhammad Bilal Zafar, Michele Donini, Dylan Slack et al.
On the Language Coverage Bias for Neural Machine Translation
Shuo Wang, Zhaopeng Tu, Zhixing Tan et al.