| CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge A Talmor*, J Herzig*, N Lourie, J Berant NAACL 2019, 2018 | 612 | 2018 |
| TAPAS: Weakly Supervised Table Parsing via Pre-training J Herzig, PK Nowak, T Müller, F Piccinno, JM Eisenschlos ACL 2020, 2020 | 322 | 2020 |
| Learning To Retrieve Prompts for In-Context Learning O Rubin, J Herzig, J Berant NAACL 2022, 2022 | 107 | 2022 |
| Span-based semantic parsing for compositional generalization J Herzig, J Berant ACL 2021, 2021 | 66 | 2021 |
| Neural semantic parsing over multiple knowledge-bases J Herzig, J Berant ACL 2017, 2017 | 65 | 2017 |
| Decoupling Structure and Lexicon for Zero-Shot Semantic Parsing J Herzig, J Berant EMNLP 2018, 2018 | 55 | 2018 |
| Improving Compositional Generalization in Semantic Parsing I Oren, J Herzig*, N Gupta*, M Gardner, J Berant Findings of EMNLP 2020, 2020 | 50 | 2020 |
| Monitoring cardiac stress using features extracted from S1 heart sounds J Herzig, A Bickel, A Eitan, N Intrator IEEE Transactions on Biomedical Engineering 62 (4), 1169-1178, 2014 | 47 | 2014 |
| TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks G Lev, M Shmueli-Scheuer, J Herzig, A Jerbi, D Konopnicki ACL 2019, 2019 | 44 | 2019 |
| A Summarization System for Scientific Documents S Erera, M Shmueli-Scheuer, G Feigenblat, OP Nakash, O Boni, ... EMNLP 2019, 2019 | 42 | 2019 |
| Unlocking compositional generalization in pre-trained models using intermediate representations J Herzig, P Shaw, MW Chang, K Guu, P Pasupat, Y Zhang arXiv preprint arXiv:2104.07478, 2021 | 41 | 2021 |
| Open Domain Question Answering over Tables via Dense Retrieval J Herzig, T Müller, S Krichene, JM Eisenschlos NAACL 2021, 2021 | 41 | 2021 |
| An author-reader influence model for detecting topic-based influencers in social media J Herzig, Y Mass, H Roitman Proceedings of the 25th ACM conference on Hypertext and social media, 46-55, 2014 | 41 | 2014 |
| Neural response generation for customer service based on personality traits J Herzig, M Shmueli-Scheuer, T Sandbank, D Konopnicki Proceedings of the 10th International Conference on Natural Language …, 2017 | 40 | 2017 |
| Classifying Emotions in Customer Support Dialogues in Social Media. J Herzig, G Feigenblat, M Shmueli-Scheuer, D Konopnicki, A Rafaeli, ... SIGDIAL Conference, 64-73, 2016 | 40 | 2016 |
| Predicting customer satisfaction in customer support conversations in social media using affective features J Herzig, G Feigenblat, M Shmueli-Scheuer, D Konopnicki, A Rafaeli Proceedings of the 2016 Conference on User Modeling Adaptation and …, 2016 | 36 | 2016 |
| Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing J Herzig, J Berant EMNLP 2019, 2019 | 35 | 2019 |
| TRUE: Re-evaluating Factual Consistency Evaluation O Honovich, R Aharoni, J Herzig, H Taitelbaum, D Kukliansy, V Cohen, ... NAACL 2022, 2022 | 31 | 2022 |
| Emotion detection from text via ensemble classification using word embeddings J Herzig, M Shmueli-Scheuer, D Konopnicki Proceedings of the ACM SIGIR international conference on theory of …, 2017 | 29 | 2017 |
| Detecting Egregious Conversations between Customers and Virtual Agents T Sandbank, M Shmueli-Scheuer, D Konopnicki, J Herzig, J Richards, ... NAACL 2018, 2017 | 25 | 2017 |
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