BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2021: all accepted papers
- Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers ↗Jason Phang, Haokun Liu, Samuel R. Bowman22 citations
- Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing ↗Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon et al.20 citations
- To what extent do human explanations of model behavior align with actual model behavior? ↗Grusha Prasad, Yixin Nie, Mohit Bansal et al.18 citations
- Enhancing Interpretable Clauses Semantically using Pretrained Word Representation ↗Rohan Kumar Yadav, Lei Jiao, Ole-Christoffer Granmo et al.17 citations
- Probing Language Models for Understanding of Temporal Expressions ↗Shivin Thukral, Kunal Kukreja, Christian Kavouras17 citations
- Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN ↗Rahma Chaabouni, Roberto Dessì, Eugene Kharitonov15 citations
- Analyzing BERT's Knowledge of Hypernymy via Prompting ↗Michael Hanna, David Mareček14 citations
- Do Language Models Know the Way to Rome? ↗Bastien Liétard, Mostafa Abdou, Anders Søgaard14 citations
- A howling success or a working sea? Testing what BERT knows about metaphors ↗Paolo Pedinotti, Eliana Di Palma, Ludovica Cerini et al.13 citations
- ALL Dolphins Are Intelligent and SOME Are Friendly: Probing BERT for Nouns' Semantic Properties and their Prototypicality ↗Marianna Apidianaki, Aina Garí Soler13 citations
- How Does BERT Rerank Passages? An Attribution Analysis with Information Bottlenecks ↗Zhiying Jiang, Raphael Tang, Ji Xin et al.11 citations
- The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty Through Generation ↗Laura Aina, Tal Linzen11 citations
- Not All Models Localize Linguistic Knowledge in the Same Place: A Layer-wise Probing on BERToids' Representations ↗Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi et al.10 citations
- Investigating Negation in Pre-trained Vision-and-language Models ↗Radina Dobreva, Frank Keller9 citations
- On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning ↗Marc Tanti, Lonneke van der Plas, Claudia Borg et al.9 citations
- Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human RatingsHendrik Schuff, Hsiu-Yu Yang, Heike Adel et al.8 citations · our summary
- Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it? ↗Tobias Norlund, Lovisa Hagström, Richard Johansson8 citations
- Not all parameters are born equal: Attention is mostly what you need ↗Nikolay Bogoychev7 citations
- Relating Neural Text Degeneration to Exposure Bias ↗Ting-Rui Chiang, Yun-Nung Chen7 citations
- BERT Has Uncommon Sense: Similarity Ranking for Word Sense BERTology ↗Luke Gessler, Nathan Schneider6 citations
- How Length Prediction Influence the Performance of Non-Autoregressive Translation? ↗Minghan Wang, Guo Jiaxin, Yuxia Wang et al.6 citations
- Screening Gender Transfer in Neural Machine Translation ↗Guillaume Wisniewski, Lichao Zhu, Nicolas Ballier et al.6 citations
- Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference ↗Hitomi Yanaka, Koji Mineshima5 citations
- How Familiar Does That Sound? Cross-Lingual Representational Similarity Analysis of Acoustic Word Embeddings ↗Badr Abdullah, Iuliia Zaitova, Tania Avgustinova et al.5 citations
- Learning Mathematical Properties of Integers ↗Maria Ryskina, Kevin Knight5 citations
- Discrete representations in neural models of spoken language ↗Bertrand Higy, Lieke Gelderloos, Afra Alishahi et al.4 citations
- The Acceptability Delta Criterion: Testing Knowledge of Language using the Gradience of Sentence Acceptability ↗Héctor Javier Vázquez Martínez4 citations
- What BERT Based Language Model Learns in Spoken Transcripts: An Empirical Study ↗Ayush Kumar, Mukuntha Narayanan Sundararaman, Jithendra Vepa4 citations
- Word Equations: Inherently Interpretable Sparse Word Embeddings through Sparse Coding ↗Adly Templeton4 citations
- Attacks against Ranking Algorithms with Text Embeddings: A Case Study on Recruitment Algorithms ↗Anahita Samadi, Debapriya Banerjee, Shirin Nilizadeh3 citations
- Multi-Layer Random Perturbation Training for improving Model Generalization Efficiently ↗Lis Kanashiro Pereira, Yuki Taya, Ichiro Kobayashi3 citations
- What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations ↗Zhouhang Xie, Jonathan Brophy, Adam Noack et al.3 citations
- An Investigation of Language Model Interpretability via Sentence Editing ↗Samuel Stevens, Yu Su2 citations
- Exploratory Model Analysis Using Data-Driven Neuron Representations ↗Daisuke Oba, Naoki Yoshinaga, Masashi Toyoda2 citations
- Test Harder than You Train: Probing with Extrapolation Splits ↗Jenny Kunz, Marco Kuhlmann2 citations
- Efficient Explanations from Empirical Explainers ↗Robert Schwarzenberg, Nils Feldhus, Sebastian Möller1 citation
- Interacting Knowledge Sources, Inspection and Analysis: Case-studies on Biomedical text processing ↗Parsa Bagherzadeh, Sabine Bergler1 citation
- ProSPer: Probing Human and Neural Network Language Model Understanding of Spatial Perspective ↗Tessa Masis, Carolyn Jane Anderson1 citation
- An in-depth look at Euclidean disk embeddings for structure preserving parsing ↗Federico Fancellu, Lan Xiao, Allan Jepson et al.
- Controlled tasks for model analysis: Retrieving discrete information from sequences ↗Ionut-Teodor Sorodoc, Gemma Boleda, Marco Baroni
- On the Limits of Minimal Pairs in Contrastive Evaluation ↗Jannis Vamvas, Rico Sennrich
- Training Dynamic based data filtering may not work for NLP datasets ↗Arka Talukdar, Monika Dagar, Prachi Gupta et al.
- Variation and generality in encoding of syntactic anomaly information in sentence embeddings ↗Qinxuan Wu, Allyson Ettinger
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