---
title: "Who cites Ioannis Konstas — 658 papers of our library"
description: "658 papers of the Elamur Research library cite the works of Ioannis Konstas, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Ioannis Konstas

693 citations of their works from 658 papers of our library (of the 149,439 whose bibliographies we read) · 113 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Ioannis Konstas](https://md.research.elamur.ai/free/en/authors/ioannis-konstas/)

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1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,967 citations*
2. **[CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge](https://md.research.elamur.ai/free/en/papers/talmor-2019-commonsenseqa-question-answering-challenge-targeting/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alon Talmor, Jonathan Herzig, Nicholas Lourie, et al.*2019 · 1,676 citations*
3. **[Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,602 citations*
4. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
5. [**Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning arXiv:1709.00103**Victor Zhong, Caiming Xiong, Richard Socher*2017 · 1,226 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2017-seq2sql-generating-structured-queries-natural/)
6. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/)
7. [**A Survey of Data Augmentation Approaches for NLP arXiv:2105.03075**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 940 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/)
8. **[Learning to Ask: Neural Question Generation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinya Du, Junru Shao, Claire Cardie*2017 · 917 citations*
9. **[TaPas: Weakly Supervised Table Parsing via Pre-training](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 847 citations*
10. [**Calibrate Before Use: Improving Few-Shot Performance of Language Models arXiv:2102.09690**Tony Z. Zhao, Eric Wallace, Shi Feng, et al.*2021 · 825 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/)
11. **[RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers](https://md.research.elamur.ai/free/en/papers/wang-2020-rat-sql-relation-aware-schema/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bailin Wang, Richard Shin, Xiaodong Liu, et al.*2020 · 753 citations*
12. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 750 citations*
13. [**CodeSearchNet Challenge: Evaluating the State of Semantic Code Search arXiv:1909.09436**Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, et al.*2020 · 656 citations*](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/)
14. **[Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/liu-2023-your-code-generated-chatgpt-really/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.*2023 · 648 citations*
15. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
16. **[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/beck-2018-graph-sequence-learning-gated-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Beck, Gholamreza Haffari, Trevor Cohn*2018 · 459 citations*
17. **[Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 433 citations*
18. **[A Transformer-based Approach for Source Code Summarization](https://md.research.elamur.ai/free/en/papers/ahmad-2020-transformer-based-approach-source-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2020 · 431 citations*
19. **[Commonsense Knowledge Mining from Pretrained Models](https://md.research.elamur.ai/free/en/papers/davison-2019-commonsense-knowledge-mining-pretrained-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joe Davison, Joshua Feldman, Alexander Rush*2019 · 413 citations*
20. **[Construction of the Literature Graph in Semantic Scholar](https://md.research.elamur.ai/free/en/papers/ammar-2018-construction-literature-graph-semantic-scholar/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, et al.*2018 · 400 citations*
21. [**SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning arXiv:1711.04436**Xiaojun Xu, Chang Liu, Dawn Song*2017 · 372 citations*](https://md.research.elamur.ai/free/en/papers/xu-2017-sqlnet-generating-structured-queries-natural/)
22. **[The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics](https://md.research.elamur.ai/free/en/papers/gehrmann-2021-gem-benchmark-natural-language-generation/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, et al.*2021 · 369 citations*
23. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
24. [**Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer**Juncen Li, Robin Jia, He He, et al.*2018 · 351 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-delete-retrieve-generate-simple-approach/)
25. **[Symbolic Knowledge Distillation: from General Language Models to Commonsense Models](https://md.research.elamur.ai/free/en/papers/west-2022-symbolic-knowledge-distillation-general-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Peter West, Chandra Bhagavatula, Jack Hessel, et al.*2022 · 349 citations*
26. **[A Graph-to-Sequence Model for AMR-to-Text Generation](https://md.research.elamur.ai/free/en/papers/song-2018-graph-sequence-model-amr-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linfeng Song, Yue Zhang, Zhiguo Wang, et al.*2018 · 330 citations*
27. [**The Adverse Effects of Code Duplication in Machine Learning Models of Code arXiv:1812.06469**Miltiadis Allamanis*2018 · 319 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2018-adverse-effects-code-duplication-machine/)
28. **[Good-Enough Compositional Data Augmentation](https://md.research.elamur.ai/free/en/papers/andreas-2020-good-enough-compositional-data-augmentation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jacob Andreas*2020 · 313 citations*
29. [**Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow arXiv:1805.08949**Pengcheng Yin, Bowen Deng, Edgar Chen, et al.*2018 · 308 citations*](https://md.research.elamur.ai/free/en/papers/yin-2018-learning-mine-aligned-code-natural/)
30. **[Constructing Datasets for Multi-hop Reading Comprehension Across Documents](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 290 citations*
31. **[Text Generation from Knowledge Graphs with Graph Transformers](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al.*2019 · 288 citations*
32. **[RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*
33. **[Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing](https://md.research.elamur.ai/free/en/papers/bogin-2019-representing-schema-structure-graph-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ben Bogin, Jonathan Berant, Matt Gardner*2019 · 272 citations*
34. **[CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases](https://md.research.elamur.ai/free/en/papers/yu-2019-cosql-conversational-text-sql-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Yu, Rui Zhang, Heyang Er, et al.*2019 · 262 citations*
35. **[Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual](https://md.research.elamur.ai/free/en/papers/he-2019-unlearn-dataset-bias-natural-language/) [Workshop on Deep Learning Approaches for Low-Resource NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-deep-learning-approaches-for-low-resource-nlp/)**He He, Sheng Zha, Haohan Wang*2019 · 260 citations*
36. **[Mapping Language to Code in Programmatic Context](https://md.research.elamur.ai/free/en/papers/iyer-2018-mapping-language-code-programmatic-context/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, et al.*2018 · 260 citations*
37. [**SocialIQA: Commonsense Reasoning about Social Interactions arXiv:1904.09728**Maarten Sap, Hannah Rashkin, Derek Chen, et al.*2019 · 259 citations*](https://md.research.elamur.ai/free/en/papers/sap-2019-socialiqa-commonsense-reasoning-about-social/)
38. **[SParC: Cross-Domain Semantic Parsing in Context](https://md.research.elamur.ai/free/en/papers/yu-2019-sparc-cross-domain-semantic-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Yu, Rui Zhang, Michihiro Yasunaga, et al.*2019 · 228 citations*
39. **[Break It Down: A Question Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 222 citations*
40. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 198 citations*
41. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations*
42. **[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://md.research.elamur.ai/free/en/papers/guo-2019-densely-connected-graph-convolutional-networks/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Yan Zhang, Zhiyang Teng, et al.*2019 · 193 citations*
43. **[Challenges in Automated Debiasing for Toxic Language Detection](https://md.research.elamur.ai/free/en/papers/zhou-2021-challenges-automated-debiasing-toxic-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, et al.*2021 · 191 citations*
44. **[LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations](https://md.research.elamur.ai/free/en/papers/cao-2021-lgesql-line-graph-enhanced-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruisheng Cao, Lu Chen, Zhi Chen, et al.*2021 · 191 citations*
45. [**CodeS: Towards Building Open-source Language Models for Text-to-SQL arXiv:2402.16347**Haoyang Li, Jing Zhang, Hanbing Liu, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-codes-towards-building-open-source/)
46. **[Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions](https://md.research.elamur.ai/free/en/papers/zhang-2019-editing-based-sql-query-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rui Zhang, Tao Yu, Heyang Er, et al.*2019 · 177 citations*
47. **[Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation](https://md.research.elamur.ai/free/en/papers/wang-2019-does-it-make-sense-why/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cunxiang Wang, Shuailong Liang, Yue Zhang, et al.*2019 · 174 citations*
48. [**A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization arXiv:1902.01069**Wonseok Hwang, Jinyeong Yim, Seunghyun Park, et al.*2019 · 170 citations*](https://md.research.elamur.ai/free/en/papers/hwang-2019-comprehensive-exploration-wikisql-table-aware/)
49. **[AMR Parsing via Graph-Sequence Iterative Inference](https://md.research.elamur.ai/free/en/papers/cai-2020-amr-parsing-graph-sequence-iterative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deng Cai, Wai Lam*2020 · 168 citations*
50. [**SantaCoder: don't reach for the stars! arXiv:2301.03988**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 167 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
51. **[Structure-Grounded Pretraining for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 167 citations*
52. **[Abstract Meaning Representation for Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/liao-2018-abstract-meaning-representation-multi-document/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Kexin Liao, Logan Lebanoff, Fei Liu*2018 · 167 citations*
53. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations*
54. [**Semantic Neural Machine Translation Using AMR**Linfeng Song, Daniel Gildea, Yue Zhang, et al.*2019 · 159 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/)
55. **[SemEval-2020 Task 4: Commonsense Validation and Explanation](https://md.research.elamur.ai/free/en/papers/wang-2020-semeval-2020-task-4-commonsense/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Cunxiang Wang, Shuailong Liang, Yili Jin, et al.*2020 · 158 citations*
56. **[Graph Pre-training for AMR Parsing and Generation](https://md.research.elamur.ai/free/en/papers/bai-2022-graph-pre-training-amr-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuefeng Bai, Yulong Chen, Yue Zhang*2022 · 153 citations*
57. **[Investigating Pretrained Language Models for Graph-to-Text Generation](https://md.research.elamur.ai/free/en/papers/ribeiro-2021-investigating-pretrained-language-models-graph/) [Workshop on Natural Language Processing for Conversational AI](https://md.research.elamur.ai/free/en/venues/nlp4convai/)**Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.*2021 · 151 citations*
58. **[CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges](https://md.research.elamur.ai/free/en/papers/zhang-2024-codeagent-enhancing-code-generation-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kechi Zhang, Jia Li, Ge Li, et al.*2024 · 150 citations*
59. **[Towards Robustness of Text-to-SQL Models against Synonym Substitution](https://md.research.elamur.ai/free/en/papers/gan-2021-robustness-text-sql-models-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujian Gan, Xinyun Chen, Qiuping Huang, et al.*2021 · 143 citations*
60. [**CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks arXiv:2105.12655**Ruchir Puri, David S. Kung, Geert Janssen, et al.*2021 · 141 citations*](https://md.research.elamur.ai/free/en/papers/puri-2021-codenet-large-scale-ai-code/)
61. **[Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/bartolo-2020-beat-ai-investigating-adversarial-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Max Bartolo, Alastair Roberts, Johannes Welbl, et al.*2020 · 141 citations*
62. **[Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations](https://md.research.elamur.ai/free/en/papers/noord-2017-neural-semantic-parsing-character-based/) [Computational Linguistics in the Netherlands Journal](https://md.research.elamur.ai/free/en/venues/computational-linguistics-in-the-netherlands-journal/)**Rik van Noord, Johan Bos*2017 · 137 citations*
63. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 135 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
64. **[Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue](https://md.research.elamur.ai/free/en/papers/balakrishnan-2019-constrained-decoding-neural-nlg-compositional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anusha Balakrishnan, Jinfeng Rao, Kartikeya Upasani, et al.*2019 · 133 citations*
65. **[Broad-Coverage Semantic Parsing as Transduction](https://md.research.elamur.ai/free/en/papers/zhang-2019-broad-coverage-semantic-parsing-as/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sheng Zhang, Xutai Ma, Kevin Duh, et al.*2019 · 124 citations*
66. **[Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization](https://md.research.elamur.ai/free/en/papers/gan-2021-exploring-underexplored-limitations-cross-domain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yujian Gan, Xinyun Chen, Matthew Purver*2021 · 123 citations*
67. **[Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-don-t-take-premise-granted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.*2019 · 123 citations*
68. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
69. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
70. **[AMR-To-Text Generation with Graph Transformer](https://md.research.elamur.ai/free/en/papers/wang-2020-amr-text-generation-graph-transformer/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tianming Wang, Xiaojun Wan, Hanqi Jin*2020 · 108 citations*
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