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2020 – today
- 2023
[c63]Boaz Carmeli, Ron Meir, Yonatan Belinkov:
Emergent Quantized Communication. AAAI 2023: 11533-11541- [c62]Ori Ram, Liat Bezalel, Adi Zicher, Yonatan Belinkov, Jonathan Berant, Amir Globerson:
What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary. ACL (1) 2023: 2481-2498 - [c61]Shadi Iskander, Kira Radinsky, Yonatan Belinkov:
Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection. ACL (Findings) 2023: 5961-5977 - [c60]Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
Parallel Context Windows for Large Language Models. ACL (1) 2023: 6383-6402 - [c59]Hadas Orgad, Yonatan Belinkov:
BLIND: Bias Removal With No Demographics. ACL (1) 2023: 8801-8821 - [c58]Ophir Münz-Manor, Michael Toker, Oren Mishali, Benny Kimelfeld, Yonatan Belinkov, Adir Cohen:
FigureOut - Automatic Detection of Metaphors in Hebrew Across the Eras. DH 2023 - [c57]Edo Dotan, Yonatan Belinkov, Oren Avram, Elya Wygoda, Noa Ecker, Michael Alburquerque, Omri Keren, Gil Loewenthal, Tal Pupko:
Multiple sequence alignment as a sequence-to-sequence learning problem. ICLR 2023 - [c56]Kevin Meng, Arnab Sen Sharma, Alex J. Andonian, Yonatan Belinkov, David Bau:
Mass-Editing Memory in a Transformer. ICLR 2023 - [i70]Hadas Orgad, Bahjat Kawar, Yonatan Belinkov:
Editing Implicit Assumptions in Text-to-Image Diffusion Models. CoRR abs/2303.08084 (2023) - [i69]Adir Rahamim, Yonatan Belinkov:
ContraSim - A Similarity Measure Based on Contrastive Learning. CoRR abs/2303.16992 (2023) - [i68]Shadi Iskander, Kira Radinsky, Yonatan Belinkov:
Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection. CoRR abs/2305.10204 (2023) - [i67]Shahar Katz, Yonatan Belinkov:
Interpreting Transformer's Attention Dynamic Memory and Visualizing the Semantic Information Flow of GPT. CoRR abs/2305.13417 (2023) - [i66]Alessandro Stolfo, Yonatan Belinkov, Mrinmaya Sachan:
Understanding Arithmetic Reasoning in Language Models using Causal Mediation Analysis. CoRR abs/2305.15054 (2023) - [i65]Dana Arad, Hadas Orgad, Yonatan Belinkov:
ReFACT: Updating Text-to-Image Models by Editing the Text Encoder. CoRR abs/2306.00738 (2023) - [i64]Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, Yoav Shoham:
Generating Benchmarks for Factuality Evaluation of Language Models. CoRR abs/2307.06908 (2023) - [i63]Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov:
Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. CoRR abs/2308.00225 (2023) - [i62]Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau
:
Linearity of Relation Decoding in Transformer Language Models. CoRR abs/2308.09124 (2023) - [i61]Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzynska, David Bau:
Unified Concept Editing in Diffusion Models. CoRR abs/2308.14761 (2023) - [i60]Michael Hanna, Yonatan Belinkov, Sandro Pezzelle:
When Language Models Fall in Love: Animacy Processing in Transformer Language Models. CoRR abs/2310.15004 (2023) - 2022
- [j9]Yonatan Belinkov:
Probing Classifiers: Promises, Shortcomings, and Advances. Comput. Linguistics 48(1): 207-219 (2022) - [c55]Joe Stacey, Yonatan Belinkov, Marek Rei:
Supervising Model Attention with Human Explanations for Robust Natural Language Inference. AAAI 2022: 11349-11357 - [c54]Kerem Zaman, Yonatan Belinkov:
A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language Inference. EMNLP 2022: 1556-1576 - [c53]Omer Antverg, Yonatan Belinkov:
On the Pitfalls of Analyzing Individual Neurons in Language Models. ICLR 2022 - [c52]Hadas Orgad, Seraphina Goldfarb-Tarrant, Yonatan Belinkov:
How Gender Debiasing Affects Internal Model Representations, and Why It Matters. NAACL-HLT 2022: 2602-2628 - [c51]Rachit Bansal, Danish Pruthi, Yonatan Belinkov:
Measures of Information Reflect Memorization Patterns. NeurIPS 2022 - [c50]Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov:
Locating and Editing Factual Associations in GPT. NeurIPS 2022 - [c49]Dimion Asael, Zachary M. Ziegler, Yonatan Belinkov:
A Generative Approach for Mitigating Structural Biases in Natural Language Inference. *SEM@NAACL-HLT 2022: 186-199 - [e4]Jasmijn Bastings, Yonatan Belinkov, Yanai Elazar, Dieuwke Hupkes, Naomi Saphra, Sarah Wiegreffe:
Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@EMNLP 2022, Abu Dhabi, United Arab Emirates (Hybrid), December 8, 2022. Association for Computational Linguistics 2022, ISBN 978-1-959429-05-0 [contents] - [i59]Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov:
Locating and Editing Factual Knowledge in GPT. CoRR abs/2202.05262 (2022) - [i58]Kerem Zaman, Yonatan Belinkov:
A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language Inference. CoRR abs/2204.05428 (2022) - [i57]Hadas Orgad, Seraphina Goldfarb-Tarrant, Yonatan Belinkov:
How Gender Debiasing Affects Internal Model Representations, and Why It Matters. CoRR abs/2204.06827 (2022) - [i56]Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, Moshe Tennenholtz:
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning. CoRR abs/2205.00445 (2022) - [i55]Omer Antverg, Eyal Ben-David, Yonatan Belinkov:
IDANI: Inference-time Domain Adaptation via Neuron-level Interventions. CoRR abs/2206.00259 (2022) - [i54]Yanai Elazar, Nora Kassner, Shauli Ravfogel, Amir Feder, Abhilasha Ravichander, Marius Mosbach, Yonatan Belinkov, Hinrich Schütze, Yoav Goldberg:
Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions. CoRR abs/2207.14251 (2022) - [i53]Kevin Meng, Arnab Sen Sharma, Alex Andonian, Yonatan Belinkov, David Bau:
Mass-Editing Memory in a Transformer. CoRR abs/2210.07229 (2022) - [i52]Rachit Bansal, Danish Pruthi, Yonatan Belinkov:
Measures of Information Reflect Memorization Patterns. CoRR abs/2210.09404 (2022) - [i51]Hadas Orgad, Yonatan Belinkov:
Choose Your Lenses: Flaws in Gender Bias Evaluation. CoRR abs/2210.11471 (2022) - [i50]Boaz Carmeli, Ron Meir, Yonatan Belinkov:
Emergent Quantized Communication. CoRR abs/2211.02412 (2022) - [i49]Ori Ram, Liat Bezalel, Adi Zicher, Yonatan Belinkov, Jonathan Berant, Amir Globerson:
What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary. CoRR abs/2212.10380 (2022) - [i48]Hadas Orgad, Yonatan Belinkov:
Debiasing NLP Models Without Demographic Information. CoRR abs/2212.10563 (2022) - [i47]Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham:
Parallel Context Windows Improve In-Context Learning of Large Language Models. CoRR abs/2212.10947 (2022) - 2021
- [c48]Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov:
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. ACL/IJCNLP (1) 2021: 1828-1843 - [c47]Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy:
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? EACL 2021: 3363-3377 - [c46]Michael Mendelson, Yonatan Belinkov:
Debiasing Methods in Natural Language Understanding Make Bias More Accessible. EMNLP (1) 2021: 1545-1557 - [c45]Yu-An Chung, Yonatan Belinkov, James R. Glass:
Similarity Analysis of Self-Supervised Speech Representations. ICASSP 2021: 3040-3044 - [c44]Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson:
Variational Information Bottleneck for Effective Low-Resource Fine-Tuning. ICLR 2021 - [c43]Victor Sanh, Thomas Wolf, Yonatan Belinkov, Alexander M. Rush:
Learning from others' mistakes: Avoiding dataset biases without modeling them. ICLR 2021 - [c42]Yana Dranker, He He, Yonatan Belinkov:
IRM - when it works and when it doesn't: A test case of natural language inference. NeurIPS 2021: 18212-18224 - [e3]Jasmijn Bastings, Yonatan Belinkov, Emmanuel Dupoux, Mario Giulianelli, Dieuwke Hupkes, Yuval Pinter, Hassan Sajjad:
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@EMNLP 2021, Punta Cana, Dominican Republic, November 11, 2021. Association for Computational Linguistics 2021, ISBN 978-1-955917-06-3 [contents] - [i46]Yonatan Belinkov:
Probing Classifiers: Promises, Shortcomings, and Alternatives. CoRR abs/2102.12452 (2021) - [i45]Joe Stacey, Yonatan Belinkov, Marek Rei:
Natural Language Inference with a Human Touch: Using Human Explanations to Guide Model Attention. CoRR abs/2104.08142 (2021) - [i44]Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson:
Variational Information Bottleneck for Effective Low-Resource Fine-Tuning. CoRR abs/2106.05469 (2021) - [i43]Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov:
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. CoRR abs/2106.06087 (2021) - [i42]Dimion Asael, Zachary M. Ziegler, Yonatan Belinkov:
A Generative Approach for Mitigating Structural Biases in Natural Language Inference. CoRR abs/2108.14006 (2021) - [i41]Michael Mendelson, Yonatan Belinkov:
Debiasing Methods in Natural Language Understanding Make Bias More Accessible. CoRR abs/2109.04095 (2021) - [i40]Omer Antverg, Yonatan Belinkov:
On the Pitfalls of Analyzing Individual Neurons in Language Models. CoRR abs/2110.07483 (2021) - 2020
- [j8]Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, James R. Glass:
On the Linguistic Representational Power of Neural Machine Translation Models. Comput. Linguistics 46(1): 1-52 (2020) - [c41]Yonatan Belinkov, Sebastian Gehrmann, Ellie Pavlick:
Interpretability and Analysis in Neural NLP. ACL (tutorial) 2020: 1-5 - [c40]John M. Wu, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James R. Glass:
Similarity Analysis of Contextual Word Representation Models. ACL 2020: 4638-4655 - [c39]Mostafa Abdou, Vinit Ravishankar, Maria Barrett, Yonatan Belinkov, Desmond Elliott, Anders Søgaard:
The Sensitivity of Language Models and Humans to Winograd Schema Perturbations. ACL 2020: 7590-7604 - [c38]Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson:
End-to-End Bias Mitigation by Modelling Biases in Corpora. ACL 2020: 8706-8716 - [c37]Nadir Durrani, Hassan Sajjad, Fahim Dalvi, Yonatan Belinkov:
Analyzing Individual Neurons in Pre-trained Language Models. EMNLP (1) 2020: 4865-4880 - [c36]Fahim Dalvi, Hassan Sajjad, Nadir Durrani, Yonatan Belinkov:
Analyzing Redundancy in Pretrained Transformer Models. EMNLP (1) 2020: 4908-4926 - [c35]Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit:
A Constructive Prediction of the Generalization Error Across Scales. ICLR 2020 - [c34]Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, Stuart M. Shieber:
Investigating Gender Bias in Language Models Using Causal Mediation Analysis. NeurIPS 2020 - [c33]Lucia Specia, Zhenhao Li, Juan Miguel Pino, Vishrav Chaudhary, Francisco Guzmán, Graham Neubig, Nadir Durrani, Yonatan Belinkov, Philipp Koehn, Hassan Sajjad, Paul Michel, Xian Li:
Findings of the WMT 2020 Shared Task on Machine Translation Robustness. WMT@EMNLP 2020: 76-91 - [e2]Afra Alishahi, Yonatan Belinkov, Grzegorz Chrupala, Dieuwke Hupkes, Yuval Pinter, Hassan Sajjad:
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@EMNLP 2020, Online, November 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-86-6 [contents] - [i39]Fahim Dalvi, Hassan Sajjad, Nadir Durrani, Yonatan Belinkov:
Exploiting Redundancy in Pre-trained Language Models for Efficient Transfer Learning. CoRR abs/2004.04010 (2020) - [i38]Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, Stuart M. Shieber:
Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias. CoRR abs/2004.12265 (2020) - [i37]Abhilasha Ravichander, Yonatan Belinkov, Eduard H. Hovy:
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? CoRR abs/2005.00719 (2020) - [i36]John M. Wu, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James R. Glass:
Similarity Analysis of Contextual Word Representation Models. CoRR abs/2005.01172 (2020) - [i35]Mostafa Abdou, Vinit Ravishankar, Maria Barrett, Yonatan Belinkov, Desmond Elliott, Anders Søgaard:
The Sensitivity of Language Models and Humans to Winograd Schema Perturbations. CoRR abs/2005.01348 (2020) - [i34]Abdelrhman Saleh, Tovly Deutsch, Stephen Casper, Yonatan Belinkov, Stuart M. Shieber:
Probing Neural Dialog Models for Conversational Understanding. CoRR abs/2006.08331 (2020) - [i33]Nadir Durrani, Hassan Sajjad, Fahim Dalvi, Yonatan Belinkov:
Analyzing Individual Neurons in Pre-trained Language Models. CoRR abs/2010.02695 (2020) - [i32]Yu-An Chung, Yonatan Belinkov, James R. Glass:
Similarity Analysis of Self-Supervised Speech Representations. CoRR abs/2010.11481 (2020) - [i31]Victor Sanh, Thomas Wolf, Yonatan Belinkov, Alexander M. Rush:
Learning from others' mistakes: Avoiding dataset biases without modeling them. CoRR abs/2012.01300 (2020)
2010 – 2019
- 2019
- [j7]Salvatore Romeo, Giovanni Da San Martino, Yonatan Belinkov, Alberto Barrón-Cedeño, Mohamed Eldesouki, Kareem Darwish, Hamdy Mubarak, James R. Glass, Alessandro Moschitti:
Language processing and learning models for community question answering in Arabic. Inf. Process. Manag. 56(2): 274-290 (2019) - [j6]Yonatan Belinkov, Alexander Magidow, Alberto Barrón-Cedeño, Avi Shmidman, Maxim Romanov:
Studying the history of the Arabic language: language technology and a large-scale historical corpus. Lang. Resour. Evaluation 53(4): 771-805 (2019) - [j5]Yonatan Belinkov, James R. Glass:
Analysis Methods in Neural Language Processing: A Survey. Trans. Assoc. Comput. Linguistics 7: 49-72 (2019) - [c32]Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, Anthony Bau, James R. Glass:
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models. AAAI 2019: 6309-6317 - [c31]Fahim Dalvi, Avery Nortonsmith, Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, James R. Glass:
NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks. AAAI 2019: 9851-9852 - [c30]Yonatan Belinkov, Adam Poliak, Stuart M. Shieber, Benjamin Van Durme, Alexander M. Rush:
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference. ACL (1) 2019: 877-891 - [c29]Hongyin Luo, Lan Jiang, Yonatan Belinkov, Jim Glass:
Improving Neural Language Models by Segmenting, Attending, and Predicting the Future. ACL (1) 2019: 1483-1493 - [c28]Jesse Vig, Yonatan Belinkov:
Analyzing the Structure of Attention in a Transformer Language Model. BlackboxNLP@ACL 2019: 63-76 - [c27]Michael Hahn, Frank Keller, Yonatan Bisk, Yonatan Belinkov:
Character-based Surprisal as a Model of Reading Difficulty in the Presence of Errors. CogSci 2019: 401-407 - [c26]Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James R. Glass:
Identifying and Controlling Important Neurons in Neural Machine Translation. ICLR (Poster) 2019 - [c25]Yonatan Belinkov, Ahmed Ali, James R. Glass:
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition. INTERSPEECH 2019: 81-85 - [c24]Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, Noah A. Smith:
Linguistic Knowledge and Transferability of Contextual Representations. NAACL-HLT (1) 2019: 1073-1094 - [c23]Nadir Durrani, Fahim Dalvi, Hassan Sajjad, Yonatan Belinkov, Preslav Nakov:
One Size Does Not Fit All: Comparing NMT Representations of Different Granularities. NAACL-HLT (1) 2019: 1504-1516 - [c22]Yonatan Belinkov, James R. Glass:
Analysis Methods in Neural Language Processing: A Survey. NAACL-HLT (1) 2019: 3348-3354 - [c21]Yonatan Belinkov, Adam Poliak, Stuart M. Shieber, Benjamin Van Durme, Alexander M. Rush:
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference. *SEM@NAACL-HLT 2019: 256-262 - [c20]Xian Li, Paul Michel, Antonios Anastasopoulos, Yonatan Belinkov, Nadir Durrani, Orhan Firat, Philipp Koehn, Graham Neubig, Juan Miguel Pino, Hassan Sajjad:
Findings of the First Shared Task on Machine Translation Robustness. WMT (2) 2019: 91-102 - [e1]Tal Linzen, Grzegorz Chrupala, Yonatan Belinkov, Dieuwke Hupkes:
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@ACL 2019, Florence, Italy, August 1, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-30-7 [contents] - [i30]Michael Hahn, Frank Keller, Yonatan Bisk, Yonatan Belinkov:
Character-based Surprisal as a Model of Human Reading in the Presence of Errors. CoRR abs/1902.00595 (2019) - [i29]Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, Noah A. Smith:
Linguistic Knowledge and Transferability of Contextual Representations. CoRR abs/1903.08855 (2019) - [i28]Hongyin Luo, Lan Jiang, Yonatan Belinkov, James R. Glass:
Improving Neural Language Models by Segmenting, Attending, and Predicting the Future. CoRR abs/1906.01702 (2019) - [i27]Mirac Suzgun, Sebastian Gehrmann, Yonatan Belinkov, Stuart M. Shieber:
LSTM Networks Can Perform Dynamic Counting. CoRR abs/1906.03648 (2019) - [i26]Jesse Vig, Yonatan Belinkov:
Analyzing the Structure of Attention in a Transformer Language Model. CoRR abs/1906.04284 (2019) - [i25]Gabriel Grand, Yonatan Belinkov:
Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects. CoRR abs/1906.08430 (2019) - [i24]Xian Li, Paul Michel, Antonios Anastasopoulos, Yonatan Belinkov, Nadir Durrani, Orhan Firat, Philipp Koehn, Graham Neubig, Juan Miguel Pino, Hassan Sajjad:
Findings of the First Shared Task on Machine Translation Robustness. CoRR abs/1906.11943 (2019) - [i23]Yonatan Belinkov, Ahmed Ali, James R. Glass:
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition. CoRR abs/1907.04224 (2019) - [i22]Yonatan Belinkov, Adam Poliak, Stuart M. Shieber, Benjamin Van Durme, Alexander M. Rush:
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference. CoRR abs/1907.04380 (2019) - [i21]Yonatan Belinkov, Adam Poliak, Stuart M. Shieber, Benjamin Van Durme, Alexander M. Rush:
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference. CoRR abs/1907.04389 (2019) - [i20]Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit:
A Constructive Prediction of the Generalization Error Across Scales. CoRR abs/1909.12673 (2019) - [i19]Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, James R. Glass:
On the Linguistic Representational Power of Neural Machine Translation Models. CoRR abs/1911.00317 (2019) - [i18]Mirac Suzgun, Sebastian Gehrmann, Yonatan Belinkov, Stuart M. Shieber:
Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages. CoRR abs/1911.03329 (2019) - 2018
- [b1]Yonatan Belinkov:
On internal language representations in deep learning: an analysis of machine translation and speech recognition. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [c19]Yonatan Belinkov, Yonatan Bisk:
Synthetic and Natural Noise Both Break Neural Machine Translation. ICLR 2018 - [c18]Adam Poliak, Yonatan Belinkov, James R. Glass, Benjamin Van Durme:
On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference. NAACL-HLT (2) 2018: 513-523 - [i17]Yonatan Belinkov, Lluís Màrquez, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James R. Glass:
Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks. CoRR abs/1801.07772 (2018) - [i16]Adam Poliak, Yonatan Belinkov, James R. Glass, Benjamin Van Durme:
On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference. CoRR abs/1804.09779 (2018) - [i15]Yonatan Belinkov, Alexander Magidow, Alberto Barrón-Cedeño, Avi Shmidman, Maxim Romanov:
Studying the History of the Arabic Language: Language Technology and a Large-Scale Historical Corpus. CoRR abs/1809.03891 (2018) - [i14]Mirac Suzgun, Yonatan Belinkov, Stuart M. Shieber:
On Evaluating the Generalization of LSTM Models in Formal Languages. CoRR abs/1811.01001 (2018) - [i13]Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James R. Glass:
Identifying and Controlling Important Neurons in Neural Machine Translation. CoRR abs/1811.01157 (2018) - [i12]Yonatan Belinkov, James R. Glass:
Analysis Methods in Neural Language Processing: A Survey. CoRR abs/1812.08951 (2018) - [i11]Fahim Dalvi, Nadir Durrani, Hassan Sajjad, Yonatan Belinkov, Anthony Bau, James R. Glass:
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models. CoRR abs/1812.09355 (2018) - [i10]