---
title: "Who cites Victoria Basmov — 292 papers of our library"
description: "292 papers of the Elamur Research library cite the works of Victoria Basmov, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/victoria-basmov/cited-by/"
---
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# Who cites Victoria Basmov

292 citations of their works from 292 papers of our library (of the 149,439 whose bibliographies we read) · 56 with a page here, the most cited first · [← Victoria Basmov](https://md.research.elamur.ai/free/en/authors/victoria-basmov/)

1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
2. [**Are NLP Models really able to Solve Simple Math Word Problems?**Arkil Patel, Satwik Bhattamishra, Navin Goyal*2021 · 890 citations*](https://md.research.elamur.ai/free/en/papers/patel-2021-are-nlp-models-really-able/)
3. **[UNIFIEDQA: Crossing Format Boundaries with a Single QA System](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Khashabi, Sewon Min, Tushar Khot, et al.*2020 · 857 citations*
4. **[Experience Grounds Language](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 439 citations*
5. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
6. [**Aligning AI With Shared Human Values arXiv:2008.02275**Dan Hendrycks, Collin Burns, Steven Basart, et al.*2020 · 395 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-aligning-ai-shared-human-values/)
7. **[Entity-Based Knowledge Conflicts in Question Answering](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 298 citations*
8. **[Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 290 citations*
9. **[Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models](https://md.research.elamur.ai/free/en/papers/wu-2021-polyjuice-generating-counterfactuals-explaining-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, et al.*2021 · 277 citations*
10. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity arXiv:2301.12867**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 249 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
11. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models arXiv:2308.01263**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
12. [**Prompting GPT-3 To Be Reliable arXiv:2210.09150**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
13. **[Towards a Unified Multi-Dimensional Evaluator for Text Generation](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ming Zhong, Yang Liu, Da Yin, et al.*2022 · 208 citations*
14. **[HateCheck: Functional Tests for Hate Speech Detection Models](https://md.research.elamur.ai/free/en/papers/rottger-2021-hatecheck-functional-tests-hate-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Röttger, Bertie Vidgen, Dong Nguyen, et al.*2021 · 204 citations*
15. **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations*
16. **[Explaining NLP Models via Minimal Contrastive Editing (MiCE)](https://md.research.elamur.ai/free/en/papers/ross-2021-explaining-nlp-models-minimal-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexis Ross, Ana Marasović, Matthew Peters*2021 · 155 citations*
17. [**TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions**Qiang Ning, Hao Wu, Rujun Han, et al.*2020 · 152 citations*](https://md.research.elamur.ai/free/en/papers/ning-2020-torque-reading-comprehension-dataset-temporal/)
18. **[Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection](https://md.research.elamur.ai/free/en/papers/chen-2021-improving-faithfulness-abstractive-summarization-contrast/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sihao Chen, Fan Zhang, Kazoo Sone, et al.*2021 · 151 citations*
19. **[Measure and Improve Robustness in NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuezhi Wang, Haohan Wang, Diyi Yang*2022 · 148 citations*
20. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
21. **[Learning from Task Descriptions](https://md.research.elamur.ai/free/en/papers/weller-2020-learning-task-descriptions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orion Weller, Nicholas Lourie, Matt Gardner, et al.*2020 · 112 citations*
22. **[CausaLM: Causal Model Explanation Through Counterfactual Language Models](https://md.research.elamur.ai/free/en/papers/feder-2021-causalm-causal-model-explanation-through/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Amir Feder, Nadav Oved, Uri Shalit, et al.*2021 · 107 citations*
23. **[Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence](https://md.research.elamur.ai/free/en/papers/chen-2022-rich-knowledge-sources-bring-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hung-Ting Chen, Michael Zhang, Eunsol Choi*2022 · 105 citations*
24. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
25. **[I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling](https://md.research.elamur.ai/free/en/papers/nie-2021-i-like-fish-especially-dolphins/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Nie, Mary Williamson, Mohit Bansal, et al.*2021 · 101 citations*
26. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 95 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
27. [**CommonsenseQA 2.0: Exposing the Limits of AI through Gamification arXiv:2201.05320**Alon Talmor, Ori Yoran, Ronan Le Bras, et al.*2022 · 94 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2022-commonsenseqa-2-0-exposing-limits/)
28. **[Tailor: Generating and Perturbing Text with Semantic Controls](https://md.research.elamur.ai/free/en/papers/ross-2022-tailor-generating-perturbing-text-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alexis Ross, Tongshuang Wu, Hao Peng, et al.*2022 · 93 citations*
29. **[NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation](https://md.research.elamur.ai/free/en/papers/dhole-2023-nl-augmenter-framework-task-sensitive/) [Northern European Journal of Language Technology](https://md.research.elamur.ai/free/en/venues/northern-european-journal-of-language-technology/)**Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.*2023 · 86 citations*
30. **[AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents](https://md.research.elamur.ai/free/en/papers/trivedi-2024-appworld-controllable-world-apps-people/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.*2024 · 80 citations*
31. **[NormBank: A Knowledge Bank of Situational Social Norms](https://md.research.elamur.ai/free/en/papers/ziems-2023-normbank-knowledge-bank-situational-social/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, et al.*2023 · 69 citations*
32. [**VALUE: Understanding Dialect Disparity in NLU**Caleb Ziems, Jiaao Chen, Camille Harris, et al.*2022 · 67 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2022-value-understanding-dialect-disparity-nlu/)
33. **[A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners](https://md.research.elamur.ai/free/en/papers/jiang-2024-peek-into-token-bias-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.*2024 · 64 citations*
34. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
35. **[Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?](https://md.research.elamur.ai/free/en/papers/balepur-2024-artifacts-or-abduction-how-do/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger*2024 · 52 citations*
36. **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations*
37. [**SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models arXiv:2311.08370**Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2023-simplesafetytests-test-suite-identifying-critical/)
38. **[Sociodemographic Bias in Language Models: A Survey and Forward Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.*2023 · 40 citations*
39. [**NOPE: A Corpus of Naturally-Occurring Presuppositions in English**Alicia Parrish, Sebastian Schuster, Alex Warstadt, et al.*2021 · 40 citations*](https://md.research.elamur.ai/free/en/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/)
40. **[Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution](https://md.research.elamur.ai/free/en/papers/emelin-2021-wino-x-multilingual-winograd-schemas/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Denis Emelin, Rico Sennrich*2021 · 35 citations*
41. **[People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://md.research.elamur.ai/free/en/papers/russell-2025-people-who-frequently-use-chatgpt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Mohit Iyyer*2025 · 33 citations*
42. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
43. **[Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design](https://md.research.elamur.ai/free/en/papers/pyatkin-2023-design-choices-crowdsourcing-implicit-discourse/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, et al.*2023 · 19 citations*
44. **[Joint Universal Syntactic and Semantic Parsing](https://md.research.elamur.ai/free/en/papers/eskin-2021-joint-universal-syntactic-semantic-parsing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Elias Stengel-Eskin, Kenton Murray, Sheng Zhang, et al.*2021 · 16 citations*
45. **[Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences](https://md.research.elamur.ai/free/en/papers/kabbara-2022-investigating-performance-transformer-based-nli/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jad Kabbara, Jackie Chi Kit Cheung*2022 · 12 citations*
46. [**The Trickle-down Impact of Reward (In-)consistency on RLHF arXiv:2309.16155**Lingfeng Shen, Sihao Chen, Linfeng Song, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-trickle-down-impact-reward-consistency/)
47. **[Coreference Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/wu-2021-coreference-reasoning-machine-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingzhu Wu, Nafise Sadat Moosavi, Dan Roth, et al.*2021 · 11 citations*
48. **[How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?](https://md.research.elamur.ai/free/en/papers/srikanth-2024-how-often-are-errors-natural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Neha Srikanth, Marine Carpuat, Rachel Rudinger*2024 · 10 citations*
49. **[Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties](https://md.research.elamur.ai/free/en/papers/masis-2022-corpus-guided-contrast-sets-morphosyntactic/) [Workshop on NLP Applications to Field Linguistics](https://md.research.elamur.ai/free/en/venues/fieldmatters/)**Tessa Masis, Anissa Neal, Lisa Green, et al.*2022 · 10 citations*
50. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
51. [**Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?**Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2023-do-pretrained-contextual-language-models/)
52. **[Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization](https://md.research.elamur.ai/free/en/papers/mersinias-2022-mitigating-dataset-artifacts-natural-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Michail Mersinias, Panagiotis Valvis*2022 · 3 citations*
53. [**Beyond Word Boundaries: A Hebrew Coreference Benchmark and an Evaluation Protocol for Morphologically Complex Text**Refael Shaked Greenfeld, Reut Tsarfaty*2026*](https://md.research.elamur.ai/free/en/papers/greenfeld-2026-beyond-word-boundaries-hebrew-coreference/)
54. [**LLMBridge: An LLM Pipeline for End-to-end Referential Bridging Resolution in English arXiv:2605.29048**Lauren Levine, Amir Zeldes*2026*](https://md.research.elamur.ai/free/en/papers/levine-2026-llmbridge-llm-pipeline-end-end/)
55. **[Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation Entanglement](https://md.research.elamur.ai/free/en/papers/singh-2026-measuring-mitigating-shortcut-reliance-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Divyajot Singh*2026*
56. **[Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-parallel-universes-parallel-languages-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Wang, Van Bach Nguyen, Yihong Liu, et al.*2026*

236 more citing papers of our library have no page here yet.

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