References

2023

• QAMPARI: : an open-domain question answering benchmark for questions with many answers from multiple paragraphs. Samuel Joseph Amouyal, Ohad Rubin, Ori Yoran, Tomer Wolfson, Jonathan Herzig, Jonathan Berant. Natural Language Reasoning and Structured Explanations Workshop@ACL, 2023.

  @inproceedings{amouyal2023qampari,
    author = {Samuel Joseph Amouyal and Ohad Rubin and Ori Yoran and Tomer Wolfson and Jonathan Herzig and Jonathan Berant},
    booktitle = {Natural Language Reasoning and Structured Explanations Workshop@ACL},
    title = {QAMPARI: : An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs},
    year = {2023},
  }
  

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• Diverse demonstrations improve in-context compositional generalization. Itay Levy, Ben Bogin, Jonathan Berant. Association for Computational Linguistics (ACL), 2023.

  @inproceedings{levy2023diverse,
    author = {Itay Levy and Ben Bogin and Jonathan Berant},
    booktitle = {Association for Computational Linguistics (ACL)},
    title = {Diverse Demonstrations Improve In-context Compositional Generalization},
    year = {2023},
  }
  

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• Crawling the internal knowledge-base of language models. Roi Cohen, Mor Geva, Jonathan Berant, Amir Globerson. Findings of the European Association for Computational Linguistics (Findings of EACL), 2023.

  @inproceedings{cohen2023kg,
    author = {Roi Cohen and Mor Geva and Jonathan Berant and Amir Globerson},
    booktitle = {Findings of the European Association for Computational Linguistics (Findings of EACL)},
    title = {Crawling the Internal Knowledge-Base of Language Models},
    year = {2023},
  }
  

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• Answering questions by meta-reasoning over multiple chains of thought. Ori Yoran, Tomer Wolfson, Ben Bogin, Uri Katz, Daniel Deutch, Jonathan Berant. Natural Language Reasoning and Structured Explanations Workshop@ACL, 2023.

  @inproceedings{yoran2023mcr,
    author = {Ori Yoran and Tomer Wolfson and Ben Bogin and Uri Katz and Daniel Deutch and Jonathan Berant},
    booktitle = {Natural Language Reasoning and Structured Explanations Workshop@ACL},
    title = {Answering Questions by Meta-Reasoning over Multiple Chains of Thought},
    year = {2023},
  }
  

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• Long-range language modeling with self-retrieval. Ohad Rubin, Jonathan Berant. arXiv preprint arXiv:2306.13421, 2023.

  @article{rubin2023rpt,
    author = {Ohad Rubin and Jonathan Berant},
    journal = {arXiv preprint arXiv:2306.13421},
    title = {Long-range Language Modeling with Self-retrieval},
    year = {2023},
  }
  

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2022

• Turning tables: generating examples from semi-structured tables for endowing language models with reasoning skills. Ori Yoran, Alon Talmor, Jonathan Berant. Association for Computational Linguistics (ACL), 2022.

  @inproceedings{yoran2022tables,
    author = {Ori Yoran and Alon Talmor and Jonathan Berant},
    booktitle = {Association for Computational Linguistics (ACL)},
    title = {Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills},
    year = {2022},
  }
  

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• Weakly supervised mapping of natural language to SQL through question decomposition. Tomer Wolfson, Jonathan Berant, Daniel Deutch. Findings of North American Association for Computational Linguistics (Findings of NAACL), 2022.

  @inproceedings{wolfson2022sql2qdmr,
    author = {Tomer Wolfson and Jonathan Berant and Daniel Deutch},
    booktitle = {Findings of North American Association for Computational Linguistics (Findings of NAACL)},
    title = {Weakly Supervised Mapping of Natural Language to {SQL} through Question Decomposition},
    year = {2022},
  }
  

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• Learning to retrieve prompts for in-context learning. Ohad Rubin, Jonathan Herzig, Jonathan Berant. North American Association for Computational Linguistics (NAACL), 2022.

  @inproceedings{rubin2022epr,
    author = {Ohad Rubin and Jonathan Herzig and Jonathan Berant},
    booktitle = {North American Association for Computational Linguistics (NAACL)},
    title = {Learning To Retrieve Prompts for In-Context Learning},
    year = {2022},
  }
  

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• SCROLLS: standardized comparison over long language sequences. Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy. Empirical Methods in Natural Language Processing (EMNLP), 2022.

  @inproceedings{shaham2022scrolls,
    author = {Uri Shaham and Elad Segal and Maor Ivgi and Avia Efrat and Ori Yoran Adi Haviv and Ankit Gupta and Wenhan Xiong and Mor Geva and Jonathan Berant and Omer Levy},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {SCROLLS: Standardized CompaRison Over Long Language Sequences},
    year = {2022},
  }
  

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• Unobserved local structures make compositional generalization hard. Ben Bogin, Shivanshu Gupta, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2022.

  @inproceedings{bogin2022unobserved,
    author = {Ben Bogin and Shivanshu Gupta and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {Unobserved Local Structures Make Compositional Generalization Hard},
    year = {2022},
  }
  

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• Scaling laws under the microscope: predicting transformer performance from small scale experiments. Maor Ivgi, Yair Carmon, Jonathan Berant. Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2022.

  @inproceedings{ivgi2022scaling,
    author = {Maor Ivgi and Yair Carmon and Jonathan Berant},
    booktitle = {Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)},
    title = {Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments},
    year = {2022},
  }
  

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• Inferring implicit relations with language models. Uri Katz, Mor Geva, Jonathan Berant. Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2022.

  @inproceedings{katz2022implicit,
    author = {Uri Katz and Mor Geva and Jonathan Berant},
    booktitle = {Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)},
    title = {Inferring Implicit Relations with Language Models},
    year = {2022},
  }
  

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• Efficient long-text understanding with short-text models. Maor Ivgi, Uri Shaham, Jonathan Berant. Transactions of the Association for Computational Linguistics (TACL), 2022.

  @article{ivgi2022sled,
    author = {Maor Ivgi and Uri Shaham and Jonathan Berant},
    journal = {Transactions of the Association for Computational Linguistics (TACL)},
    title = {Efficient Long-Text Understanding with Short-Text Models},
    volume = {4},
    year = {2022},
  }
  

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• Training vision-language models with less bimodal supervision. Elad Segal, Ben Bogin, Jonathan Berant. Automated Knowledge Base Construction (AKBC), 2022.

  @inproceedings{segal2022bimdal,
    author = {Elad Segal and Ben Bogin and Jonathan Berant},
    booktitle = {Automated Knowledge Base Construction (AKBC)},
    title = {Training Vision-Language Models with Less Bimodal Supervision},
    year = {2022},
  }
  

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• Simplifying and understanding state space models with diagonal linear rnns. Ankit Gupta, Harsh Mehta, Jonathan Berant. arXiv preprint arXiv:2212.00768, 2022.

  @article{gupta2022dlr,
    author = {Ankit Gupta and Harsh Mehta and Jonathan Berant},
    journal = {arXiv preprint arXiv:2212.00768},
    title = {Simplifying and Understanding State Space Models with Diagonal Linear RNNs},
    year = {2022},
  }
  

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2021

• Latent compositional representations improve systematic generalization in grounded question answering. Ben Bogin, Sanjay Subramanian, Matt Gardner, Jonathan Berant. Transactions of the Association for Computational Linguistics (TACL), 2021.

  @article{bogin2021latent,
    author = {Ben Bogin and Sanjay Subramanian and Matt Gardner and Jonathan Berant},
    journal = {Transactions of the Association for Computational Linguistics (TACL)},
    pages = {195--210},
    title = {Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering},
    volume = {9},
    year = {2021},
  }
  

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• Span-based semantic parsing for compositional generalization. Jonathan Herzig, Jonathan Berant. Association for Computational Linguistics (ACL), 2021.

  @inproceedings{herzig2021span,
    author = {Jonathan Herzig and Jonathan Berant},
    booktitle = {Association for Computational Linguistics (ACL)},
    title = {Span-based Semantic Parsing for Compositional Generalization},
    year = {2021},
  }
  

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• Scene graph to image generation with contextualized object layout refinement. Maor Ivgi, Yaniv Benny, Avichai Ben-David, Jonathan Berant, Lior Wolf. IEEE International Conference on Image Processing (ICIP), 2021.

  @inproceedings{ivgi2021scenegraph,
    author = {Maor Ivgi and Yaniv Benny and Avichai Ben-David and Jonathan Berant and Lior Wolf},
    booktitle = {IEEE International Conference on Image Processing (ICIP)},
    title = {Scene Graph to Image Generation with Contextualized Object Layout Refinement},
    year = {2021},
  }
  

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• Evaluating the evaluation of diversity in natural language generation. Guy Tevet, Jonathan Berant. European Association for Computational Linguistics (EACL), 2021.

  @inproceedings{tevet2021diversity,
    author = {Guy Tevet and Jonathan Berant},
    booktitle = {European Association for Computational Linguistics (EACL)},
    title = {Evaluating the Evaluation of Diversity in Natural Language Generation},
    year = {2021},
  }
  

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• Did aristotle use a laptop?a question answering benchmark with implicit reasoning strategies. Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, Jonathan Berant. Transactions of the Association for Computational Linguistics (TACL), 2021.

  @article{geva2021strategyqa,
    author = {Mor Geva and Daniel Khashabi and Elad Segal and Tushar Khot and Dan Roth and Jonathan Berant},
    journal = {Transactions of the Association for Computational Linguistics (TACL)},
    pages = {346--361},
    title = {Did Aristotle Use a Laptop?A Question Answering Benchmark with Implicit Reasoning Strategies},
    volume = {9},
    year = {2021},
  }
  

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• SmBoP: semi-autoregressive bottom-up semantic parsing. Ohad Rubin, Jonathan Berant. North American Association for Computational Linguistics (NAACL), 2021.

  @inproceedings{rubin2021smbop,
    author = {Ohad Rubin and Jonathan Berant},
    booktitle = {North American Association for Computational Linguistics (NAACL)},
    title = {Sm{B}o{P}: Semi-autoregressive Bottom-up Semantic Parsing},
    year = {2021},
  }
  

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• MultiModalQA: complex question answering over text, tables and images. Alon Talmor, Ori Yoran, Amnon Catav, Dan Lahav, Yizhong Wang, Akari Asai, Gabriel Ilharco, Hannaneh Hajishirzi, Jonathan Berant. International Conference on Learning Representations (ICLR), 2021.

  @inproceedings{talmor2021multimodalqa,
    author = {Alon Talmor and Ori Yoran and Amnon Catav and Dan Lahav and Yizhong Wang and Akari Asai and Gabriel Ilharco and Hannaneh Hajishirzi and Jonathan Berant},
    booktitle = {International Conference on Learning Representations (ICLR)},
    title = {MultiModalQA: Complex Question Answering Over Text, Tables And Images},
    year = {2021},
  }
  

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• Achieving model robustness through discrete adversarial training. Maor Ivgi, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2021.

  @inproceedings{ivgi2021robustness,
    author = {Maor Ivgi and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {Achieving Model Robustness through Discrete Adversarial Training},
    year = {2021},
  }
  

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• What's in your head? emergent behaviour in multi-task transformer models. Mor Geva, Uri Katz, Aviv Ben-Arie, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2021.

  @inproceedings{geva2021head,
    author = {Mor Geva and Uri Katz and Aviv Ben-Arie and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {What's in your Head? Emergent Behaviour in Multi-Task Transformer Models},
    year = {2021},
  }
  

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• Question decomposition with dependency graphs. Matan Hasson, Jonathan Berant. Automated Knowledge Base Construction (AKBC), 2021.

  @inproceedings{hasson2021qdmr,
    author = {Matan Hasson and Jonathan Berant},
    booktitle = {Automated Knowledge Base Construction (AKBC)},
    title = {Question Decomposition with Dependency Graphs},
    year = {2021},
  }
  

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• CommonsenseQA 2.0: exposing the limits of AI through gamification. Alon Talmor, Ori Yoran, Ronan Le Bras, Chandra Bhagavatula, Yoav Goldberg, Yejin Choi, Jonathan Berant. Advances in Neural Information Processing Systems (NeurIPS), 2021. Oral presentation.

  @inproceedings{talmor2021csqa,
    author = {Alon Talmor and Ori Yoran and Ronan Le Bras and Chandra Bhagavatula and Yoav Goldberg and Yejin Choi and Jonathan Berant},
    booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Commonsense{QA} 2.0: Exposing the Limits of {AI} through Gamification},
    year = {2021},
  }
  

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• Break, perturb, build: automatic perturbation of reasoning pathsthrough question decomposition. Mor Geva, Tomer Wolfson, Jonathan Berant. Transactions of the Association for Computational Linguistics (TACL), 2021.

  @article{geva2021bpb,
    author = {Mor Geva and Tomer Wolfson and Jonathan Berant},
    journal = {Transactions of the Association for Computational Linguistics (TACL)},
    title = {Break, Perturb, Build: Automatic Perturbation of Reasoning Pathsthrough Question Decomposition},
    volume = {1},
    year = {2021},
  }
  

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• COVR: a test-bed for visually grounded compositional generalization with real images. Ben Bogin, Shivanshu Gupta, Matt Gardner, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2021.

  @inproceedings{bogin2021covr,
    author = {Ben Bogin and Shivanshu Gupta and Matt Gardner and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {{COVR}: A Test-Bed for Visually Grounded Compositional Generalization with Real Images},
    year = {2021},
  }
  

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• Finding needles in a haystack: sampling structurally-diverse training sets from synthetic data for compositional generalization. Inbar Oren, Jonathan Herzig, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2021.

  @inproceedings{oren2021needles,
    author = {Inbar Oren and Jonathan Herzig and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization},
    year = {2021},
  }
  

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2020

• oLMpics -- on what language model pre-training captures. Alon Talmor, Yanai Elazar, Yoav Goldberg, Jonathan Berant. Transactions of the Association for Computational Linguistics (TACL), 2020.

  @article{talmor2020olmpics,
    author = {Alon Talmor and Yanai Elazar and Yoav Goldberg and Jonathan Berant},
    journal = {Transactions of the Association for Computational Linguistics (TACL)},
    pages = {743--758},
    title = {oLMpics -- On what Language Model Pre-training Captures},
    volume = {8},
    year = {2020},
  }
  

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• Evaluating NLP models via contrast sets. Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou. Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2020.

  @inproceedings{gardner2020contrast,
    author = {Matt Gardner and Yoav Artzi and Victoria Basmova and Jonathan Berant and Ben Bogin and Sihao Chen and Pradeep Dasigi and Dheeru Dua and Yanai Elazar and Ananth Gottumukkala and Nitish Gupta and Hanna Hajishirzi and Gabriel Ilharco and Daniel Khashabi and Kevin Lin and Jiangming Liu and Nelson F. Liu and Phoebe Mulcaire and Qiang Ning and Sameer Singh and Noah A. Smith and Sanjay Subramanian and Reut Tsarfaty and Eric Wallace and Ally Zhang and Ben Zhou},
    booktitle = {Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)},
    title = {Evaluating {NLP} Models via Contrast Sets},
    year = {2020},
  }
  

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• Injecting numerical reasoning skills into language models. Mor Geva, Ankit Gupta, Jonathan Berant. Association for Computational Linguistics (ACL), 2020.

  @inproceedings{geva2020injecting,
    author = {Mor Geva and Ankit Gupta and Jonathan Berant},
    booktitle = {Association for Computational Linguistics (ACL)},
    title = {Injecting Numerical Reasoning Skills into Language Models},
    year = {2020},
  }
  

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• Explaining question answering models through text generation. Veronica Latcinnik, Jonathan Berant. arXiv preprint arXiv:2004.05569, 2020.

  @article{latcinnik2020explaining,
    author = {Veronica Latcinnik and Jonathan Berant},
    journal = {arXiv preprint arXiv:2004.05569},
    title = {Explaining Question Answering Models through Text Generation},
    year = {2020},
  }
  

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• Obtaining faithful interpretations from compositional neural networks. Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, Matt Gardner. Association for Computational Linguistics (ACL), 2020.

  @inproceedings{subramanian2020interpretability,
    author = {Sanjay Subramanian and Ben Bogin and Nitish Gupta and Tomer Wolfson and Sameer Singh and Jonathan Berant and Matt Gardner},
    booktitle = {Association for Computational Linguistics (ACL)},
    title = {Obtaining Faithful Interpretations from Compositional Neural Networks},
    year = {2020},
  }
  

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• A simple and effective model for answering multi-span questions. Elad Segal, Avia Efrat, Mor Shoham, Amir Globerson, Jonathan Berant. Empirical Methods in Natural Language Processing (EMNLP), 2020.

  @inproceedings{segal2020multispan,
    author = {Elad Segal and  Avia Efrat and Mor Shoham and Amir Globerson and Jonathan Berant},
    booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
    title = {A Simple and Effective Model for Answering Multi-span Questions},
    year = {2020},
  }
  

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• Leaf-Of-Thought: teaching pre-trained models to systematically reason over implicit knowledge. Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, Jonathan Berant. Advances in Neural Information Processing Systems (NeurIPS), 2020. Spotlight talk (3% of submissions).

  @inproceedings{talmor2020teaching,
    author = {Alon Talmor and Oyvind Tafjord and Peter Clark and Yoav Goldberg and Jonathan Berant},
    booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Leaf-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge},
    year = {2020},
  }
  

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• Improving compositional generalization in semantic parsing. Inbar Oren, Jonathan Herzig, Nitish Gupta, Matt Gardner, Jonathan Berant. Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP), 2020.

  @inproceedings{oren2020compositionality,
    author = {Inbar Oren and Jonathan Herzig and Nitish Gupta and Matt Gardner and Jonathan Berant},
    booktitle = {Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)},
    title = {Improving Compositional Generalization in Semantic Parsing},
    year = {2020},
  }
  

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