Papers
Closing Brackets with Recurrent Neural Networks
Natalia Skachkova, Thomas Trost, Dietrich Klakow
Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items
Jaap Jumelet, Dieuwke Hupkes
What do RNN Language Models Learn about Filler–Gap Dependencies?
Ethan Wilcox, Roger Levy, Takashi Morita et al.
Learning and Evaluating Sparse Interpretable Sentence Embeddings
Valentin Trifonov, Octavian-Eugen Ganea, Anna Potapenko et al.
Introspection for convolutional automatic speech recognition
Andreas Krug, Sebastian Stober
An Operation Sequence Model for Explainable Neural Machine Translation
Felix Stahlberg, Danielle Saunders, Bill Byrne
Analysing the potential of seq-to-seq models for incremental interpretation in task-oriented dialogue
Dieuwke Hupkes, Sanne Bouwmeester, Raquel Fernández
‘Indicatements’ that character language models learn English morpho-syntactic units and regularities
Yova Kementchedjhieva, Adam Lopez
Interpreting Neural Networks with Nearest Neighbors
Eric Wallace, Shi Feng, Jordan Boyd-Graber
Interpretable Neural Architectures for Attributing an Ad’s Performance to its Writing Style
Reid Pryzant, Sugato Basu, Kazoo Sone
Evaluating the Ability of LSTMs to Learn Context-Free Grammars
Luzi Sennhauser, Robert Berwick
Rearranging the Familiar: Testing Compositional Generalization in Recurrent Networks
João Loula, Marco Baroni, Brenden Lake
Can LSTM Learn to Capture Agreement? The Case of Basque
Shauli Ravfogel, Yoav Goldberg, Francis Tyers
Rule induction for global explanation of trained models
Madhumita Sushil, Simon Šuster, Walter Daelemans
Unsupervised Token-wise Alignment to Improve Interpretation of Encoder-Decoder Models
Shun Kiyono, Sho Takase, Jun Suzuki et al.
Linguistic representations in multi-task neural networks for ellipsis resolution
Ola Rønning, Daniel Hardt, Anders Søgaard
Understanding Convolutional Neural Networks for Text Classification
Alon Jacovi, Oren Sar Shalom, Yoav Goldberg
Jump to better conclusions: SCAN both left and right
Jasmijn Bastings, Marco Baroni, Jason Weston et al.
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis
Jose Camacho-Collados, Mohammad Taher Pilehvar
Evaluating Textual Representations through Image Generation
Graham Spinks, Marie-Francine Moens
Nightmare at test time: How punctuation prevents parsers from generalizing
Anders Søgaard, Miryam de Lhoneux, Isabelle Augenstein
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures
Danilo Croce, Daniele Rossini, Roberto Basili
Analyzing Learned Representations of a Deep ASR Performance Prediction Model
Zied Elloumi, Laurent Besacier, Olivier Galibert et al.
When does deep multi-task learning work for loosely related document classification tasks?
Emma Kerinec, Chloé Braud, Anders Søgaard