---
title: "Who cites An Analysis of Natural Language Inference…"
description: "The papers of the Elamur Research library that cite «An Analysis of Natural Language Inference Benchmarks through the Lens of Negation», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/hossain-2020-analysis-natural-language-inference-benchmarks/cited-by/"
---
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# Who cites «An Analysis of Natural Language Inference Benchmarks through the Lens of Negation»

68 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/hossain-2020-analysis-natural-language-inference-benchmarks/)

1. [As Easy as Rocket Science: Assessing the Ability of Large Language Models to Interpret Negation in Figurative Language](https://aclanthology.org/2026.tacl-1.83/) *— 2026 · Transactions of the Association for Computational Linguistics*
2. [Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding](https://aclanthology.org/2026.findings-acl.578/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
3. [JSTS-Neg: Japanese Semantic Textual Similarity Dataset for Evaluating Negation Understanding Ability](https://aclanthology.org/2026.lrec-1.942/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
4. [NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference](https://aclanthology.org/2026.lrec-1.97/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
5. [Negation-Aware Data Augmentation for Portuguese Natural Language Inference](https://aclanthology.org/2026.propor-1.14/) *— 2026 · Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1*
6. [Synthetic Data Fine-Tuning for Effective Team Formation in Enterprises](https://aclanthology.org/2026.eacl-industry.46/) *— 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 5: Industry Track)*
7. [Thunder-KoNUBench: A Corpus-Aligned Benchmark for Korean Negation Understanding](https://aclanthology.org/2026.findings-acl.324/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
8. [Thunder-NUBench: A Benchmark for LLMs” Sentence-Level Negation Understanding](https://aclanthology.org/2026.findings-eacl.250/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
9. [A Comprehensive Taxonomy of Negation for NLP and Neural Retrievers](https://aclanthology.org/2025.findings-emnlp.839/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
10. [D-Neg: Syntax-Aware Graph Reasoning for Negation Detection](https://aclanthology.org/2025.findings-ijcnlp.89/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
11. [Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation](https://aclanthology.org/2025.trustnlp-main.37/) *— 2025 · Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025)*
12. [Linking language model predictions to human behaviour on scalar implicatures](https://aclanthology.org/2025.neusymbridge-1.10/) *— 2025 · Proceedings of Bridging Neurons and Symbols for Natural Language Processing and Knowledge Graphs Reasoning @ COLING 2025*
13. [Making Language Models Robust Against Negation](https://aclanthology.org/2025.naacl-long.413/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
14. [NegVQA: Can Vision Language Models Understand Negation?](https://aclanthology.org/2025.findings-acl.191/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
15. [Superfluous Instruction: Vulnerabilities Stemming from Task-Specific Superficial Expressions in Instruction Templates](https://aclanthology.org/2025.knowllm-1.12/) *— 2025 · Proceedings of the 3rd Workshop on Towards Knowledgeable Foundation Models (KnowFM)*
16. [This is not a Disimprovement: Improving Negation Reasoning in Large Language Models via Prompt Engineering](https://aclanthology.org/2025.findings-emnlp.761/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
17. [Benchmark Transparency: Measuring the Impact of Data on Evaluation](https://aclanthology.org/2024.naacl-long.86/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
18. [FReND: A French Resource of Negation Data](https://aclanthology.org/2024.lrec-main.658/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
19. [It is not True that Transformers are Inductive Learners: Probing NLI Models with External Negation](https://aclanthology.org/2024.eacl-long.116/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
20. [Recognizing Value Resonance with Resonance-Tuned RoBERTa Task Definition, Experimental Validation, and Robust Modeling](https://aclanthology.org/2024.lrec-main.1195/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
21. [Revisiting subword tokenization: A case study on affixal negation in large language models](https://aclanthology.org/2024.naacl-long.284/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
22. [To Learn or Not to Learn: Replaced Token Detection for Learning the Meaning of Negation](https://aclanthology.org/2024.lrec-main.1411/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
23. [Assessing Step-by-Step Reasoning against Lexical Negation: A Case Study on Syllogism](https://aclanthology.org/2023.emnlp-main.912/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
24. [Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models](https://aclanthology.org/2023.findings-acl.472/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
25. [Can Pretrained Language Models (Yet) Reason Deductively?](https://aclanthology.org/2023.eacl-main.106/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
26. [Consistency Analysis of ChatGPT](https://aclanthology.org/2023.emnlp-main.991/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
27. [Cross-Platform and Cross-Domain Abusive Language Detection with Supervised Contrastive Learning](https://aclanthology.org/2023.woah-1.9/) *— 2023 · The 7th Workshop on Online Abuse and Harms (WOAH)*
28. [Evaluating Large Language Models at Evaluating Instruction Following](https://arxiv.org/abs/2310.07641) *— 2023 · arXiv:2310.07641*
29. [Formal Proofs as Structured Explanations: Proposing Several Tasks on Explainable Natural Language Inference](https://arxiv.org/abs/2311.08637) *— 2023 · arXiv:2311.08637*
30. [Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary](https://aclanthology.org/2023.emnlp-main.527/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
31. [It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance](https://aclanthology.org/2023.findings-acl.202/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
32. [Language models are not naysayers: An analysis of language models on negation benchmarks](https://arxiv.org/abs/2306.08189) *— 2023 · arXiv:2306.08189*
33. [Limits for learning with language models](https://aclanthology.org/2023.starsem-1.22/) *— 2023 · Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)*
34. [Measuring Consistency in Text-based Financial Forecasting Models](https://aclanthology.org/2023.acl-long.769/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
35. [Multi-VALUE: A Framework for Cross-Dialectal English NLP](https://md.research.elamur.ai/free/en/papers/ziems-2023-multi-value-framework-cross-dialectal/) *— our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [NLMs: Augmenting Negation in Language Models](https://aclanthology.org/2023.findings-emnlp.873/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
37. [Natural Language Reasoning, A Survey](https://arxiv.org/abs/2303.14725) *— 2023 · arXiv:2303.14725*
38. [PASTA: A Dataset for Modeling PArticipant STAtes in Narratives](https://aclanthology.org/2023.tacl-1.73/) *— 2023 · Transactions of the Association for Computational Linguistics*
39. [ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning](https://aclanthology.org/2023.acl-short.154/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
40. [SpaceNLI: Evaluating the Consistency of Predicting Inferences In Space](https://aclanthology.org/2023.naloma-1.2/) *— 2023 · Proceedings of the 4th Natural Logic Meets Machine Learning Workshop*
41. [Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference](https://aclanthology.org/2023.nlrse-1.12/) *— 2023 · Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE)*
42. [ANLIzing the Adversarial Natural Language Inference Dataset](https://aclanthology.org/2022.scil-1.3/) *— 2022 · Proceedings of the Society for Computation in Linguistics 2022*
43. [An Analysis of Negation in Natural Language Understanding Corpora](https://aclanthology.org/2022.acl-short.81/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
44. [BECEL: Benchmark for Consistency Evaluation of Language Models](https://aclanthology.org/2022.coling-1.324/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
45. [Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence](https://aclanthology.org/2022.findings-naacl.156/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
46. [CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation](https://aclanthology.org/2022.emnlp-main.598/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
47. [Context Matters: A Pragmatic Study of PLMs” Negation Understanding](https://aclanthology.org/2022.acl-long.315/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [Developmental Negation Processing in Transformer Language Models](https://aclanthology.org/2022.acl-short.60/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
49. [E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning](https://aclanthology.org/2022.findings-acl.311/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
50. [Generalized Quantifiers as a Source of Error in Multilingual NLU Benchmarks](https://aclanthology.org/2022.naacl-main.359/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
51. [Improving negation detection with negation-focused pre-training](https://aclanthology.org/2022.naacl-main.309/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
52. [InferES : A Natural Language Inference Corpus for Spanish Featuring Negation-Based Contrastive and Adversarial Examples](https://aclanthology.org/2022.coling-1.340/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
53. [It Is Not Easy To Detect Paraphrases: Analysing Semantic Similarity With Antonyms and Negation Using the New SemAntoNeg Benchmark](https://aclanthology.org/2022.blackboxnlp-1.20/) *— 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
54. [KoBEST: Korean Balanced Evaluation of Significant Tasks](https://aclanthology.org/2022.coling-1.325/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
55. [LogiTorch: A PyTorch-based library for logical reasoning on natural language](https://aclanthology.org/2022.emnlp-demos.25/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
56. [Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation](https://aclanthology.org/2022.aacl-main.65/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
57. [TINA: Textual Inference with Negation Augmentation](https://aclanthology.org/2022.findings-emnlp.301/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
58. [Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns](https://arxiv.org/abs/2201.07614) *— 2022 · arXiv:2201.07614*
59. [A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs](https://aclanthology.org/2021.conll-1.19/) *— 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
60. [Can vectors read minds better than experts? Comparing data augmentation strategies for the automated scoring of children's mindreading ability](https://aclanthology.org/2021.acl-long.96/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
61. [Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI](https://aclanthology.org/2021.emnlp-main.303/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
62. [Dynabench: Rethinking Benchmarking in NLP](https://aclanthology.org/2021.naacl-main.324/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
63. [IndoNLI: A Natural Language Inference Dataset for Indonesian](https://aclanthology.org/2021.emnlp-main.821/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
64. [Investigating Negation in Pre-trained Vision-and-language Models](https://aclanthology.org/2021.blackboxnlp-1.27/) *— 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
65. [Negation-Instance Based Evaluation of End-to-End Negation Resolution](https://aclanthology.org/2021.conll-1.41/) *— 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
66. [Plongements Interprétables pour la Détection de Biais Cachés (Interpretable Embeddings for Hidden Biases Detection)](https://aclanthology.org/2021.jeptalnrecital-taln.6/) *— 2021 · Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
67. [Understanding by Understanding Not: Modeling Negation in Language Models](https://aclanthology.org/2021.naacl-main.102/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
68. [It”s not a Non-Issue: Negation as a Source of Error in Machine Translation](https://aclanthology.org/2020.findings-emnlp.345/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*