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# Who cites «WordNet: A Lexical Database for English» · page 3

2080 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/lex-1994-miller-wordnet/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-2/) · **3** · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-6/) · [7](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-7/) · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-12/) · [13](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-13/) · [14](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-14/) · [15](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-15/) · [16](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-16/) · [17](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-17/) · [18](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-18/) · [19](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-19/) · [20](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-20/) · [21](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lex-1994-miller-wordnet-21/)

1. [Data Augmentation for Radiology Report Simplification](https://aclanthology.org/2023.findings-eacl.144/) *— 2023 · Findings of the Association for Computational Linguistics: EACL 2023*
2. [Dense Retrieval as Indirect Supervision for Large-space Decision Making](https://aclanthology.org/2023.findings-emnlp.1002/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
3. [Dense-ATOMIC: Towards Densely-connected ATOMIC with High Knowledge Coverage and Massive Multi-hop Paths](https://aclanthology.org/2023.acl-long.742/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
4. [Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation Extraction](https://aclanthology.org/2023.acl-long.354/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
5. [Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering](https://aclanthology.org/2023.findings-acl.835/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
6. [Distractor Generation for Fill-in-the-Blank Exercises by Question Type](https://aclanthology.org/2023.acl-srw.38/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
7. [Dive into Deep Learning](https://d2l.ai/) *— 2023 · textbook*
8. [Do language models have coherent mental models of everyday things?](https://aclanthology.org/2023.acl-long.106/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
9. [Dynamic Heterogeneous-Graph Reasoning with Language Models and Knowledge Representation Learning for Commonsense Question Answering](https://aclanthology.org/2023.acl-long.785/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [Expanding Scope: Adapting English Adversarial Attacks to Chinese](https://aclanthology.org/2023.trustnlp-1.24/) *— 2023 · Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)*
11. [Expectations over Unspoken Alternatives Predict Pragmatic Inferences](https://md.mova.elamur.ai/free/en/docs/papers/hu-2023-expectations-over-unspoken-alternatives-predict/) *— our card · 2023*
12. [Exploring Non-Verbal Predicates in Semantic Role Labeling: Challenges and Opportunities](https://md.mova.elamur.ai/free/en/docs/papers/orlando-2023-exploring-non-verbal-predicates-semantic/) *— our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
13. [FactKG: Fact Verification via Reasoning on Knowledge Graphs](https://aclanthology.org/2023.acl-long.895/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [GBT: Generative Boosting Training Approach for Paraphrase Identification](https://aclanthology.org/2023.findings-emnlp.405/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
15. [Generating Commonsense Counterfactuals for Stable Relation Extraction](https://aclanthology.org/2023.emnlp-main.344/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
16. [Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT](https://arxiv.org/abs/2304.11116) *— 2023 · arXiv:2304.11116*
17. [GreenKGC: A Lightweight Knowledge Graph Completion Method](https://aclanthology.org/2023.acl-long.591/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
18. [Hence, Socrates is mortal: A Benchmark for Natural Language Syllogistic Reasoning](https://aclanthology.org/2023.findings-acl.148/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
19. [IDAS: Intent Discovery with Abstractive Summarization](https://aclanthology.org/2023.nlp4convai-1.7/) *— 2023 · Proceedings of the 5th Workshop on NLP for Conversational AI (NLP4ConvAI 2023)*
20. [Improving Knowledge Graph Completion with Generative Hard Negative Mining](https://aclanthology.org/2023.findings-acl.362/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
21. [Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training](https://aclanthology.org/2023.findings-acl.770/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
22. [Interactive-Chain-Prompting: Ambiguity Resolution for Crosslingual Conditional Generation with Interaction](https://aclanthology.org/2023.ijcnlp-main.31/) *— 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Internet Explorer: Targeted Representation Learning on the Open Web](https://arxiv.org/abs/2302.14051) *— 2023 · arXiv:2302.14051*
24. [Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis](https://md.mova.elamur.ai/free/en/docs/papers/lex-2023-giulianelli-definition-generation-senses/) *— our card · 2023 · ACL 2023 (Toronto)*
25. [KG-BERTScore: Incorporating Knowledge Graph into BERTScore for Reference-Free Machine Translation Evaluation](https://arxiv.org/abs/2301.12699) *— 2023 · arXiv:2301.12699*
26. [KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion](https://aclanthology.org/2023.findings-emnlp.580/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
27. [Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generation](https://arxiv.org/abs/2301.02275) *— 2023 · arXiv:2301.02275*
28. [Linearity of Relation Decoding in Transformer Language Models](https://arxiv.org/abs/2308.09124) *— 2023 · arXiv:2308.09124*
29. [MWE as WSD: Solving Multiword Expression Identification with Word Sense Disambiguation](https://aclanthology.org/2023.findings-emnlp.14/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
30. [Making Presentation Math Computable: A Context-Sensitive Approach for Translating LaTeX to Computer Algebra Systems](https://link.springer.com/book/10.1007/978-3-658-40473-4) *— 2023 · monograph*
31. [Modeling Cross-Cultural Pragmatic Inference with Codenames Duet](https://aclanthology.org/2023.findings-acl.410/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
32. [Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs](https://aclanthology.org/2023.emnlp-main.800/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
33. [NEWTON: Are Large Language Models Capable of Physical Reasoning?](https://aclanthology.org/2023.findings-emnlp.652/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
34. [Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis](https://aclanthology.org/2023.emnlp-main.277/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
35. [Nonlinear Structural Equation Model Guided Gaussian Mixture Hierarchical Topic Modeling](https://aclanthology.org/2023.acl-long.578/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [OPI at SemEval-2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation](https://aclanthology.org/2023.semeval-1.22/) *— 2023 · Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)*
37. [ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer](https://arxiv.org/abs/2308.15459) *— 2023 · arXiv:2308.15459*
38. [Penguins Don''t Fly: Reasoning about Generics through Instantiations and Exceptions](https://aclanthology.org/2023.eacl-main.192/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
39. [Predicting Terms in IS-A Relations with Pre-trained Transformers](https://aclanthology.org/2023.findings-ijcnlp.12/) *— 2023 · Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings)*
40. [Probing the ``Creativity'''' of Large Language Models: Can models produce divergent semantic association?](https://aclanthology.org/2023.findings-emnlp.858/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
41. [Prompted Opinion Summarization with GPT-3.5](https://aclanthology.org/2023.findings-acl.591/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
42. [QA-NatVer: Question Answering for Natural Logic-based Fact Verification](https://aclanthology.org/2023.emnlp-main.521/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
43. [QADYNAMICS: Training Dynamics-Driven Synthetic QA Diagnostic for Zero-Shot Commonsense Question Answering](https://aclanthology.org/2023.findings-emnlp.1023/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
44. [Query2doc: Query Expansion with Large Language Models](https://aclanthology.org/2023.emnlp-main.585/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
45. [RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset](https://arxiv.org/abs/2306.09802) *— 2023 · arXiv:2306.09802*
46. [RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question](https://aclanthology.org/2023.findings-acl.428/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
47. [ReCode: Robustness Evaluation of Code Generation Models](https://aclanthology.org/2023.acl-long.773/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization](https://aclanthology.org/2023.findings-eacl.90/) *— 2023 · Findings of the Association for Computational Linguistics: EACL 2023*
49. [Relational Sentence Embedding for Flexible Semantic Matching](https://aclanthology.org/2023.repl4nlp-1.20/) *— 2023 · Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)*
50. [Rethinking with Retrieval: Faithful Large Language Model Inference](https://arxiv.org/abs/2301.00303) *— 2023 · arXiv:2301.00303*
51. [SRCB at SemEval-2023 Task 1: Prompt Based and Cross-Modal Retrieval Enhanced Visual Word Sense Disambiguation](https://aclanthology.org/2023.semeval-1.60/) *— 2023 · Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)*
52. [Scalable Performance Analysis for Vision-Language Models](https://aclanthology.org/2023.starsem-1.26/) *— 2023 · Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)*
53. [SimpLex: a lexical text simplification architecture](https://arxiv.org/abs/2304.07002) *— 2023 · arXiv:2304.07002 · Neural Computing and Applications, 35(8):6265-6280, 2023*
54. [Simple and Effective Multi-Token Completion from Masked Language Models](https://aclanthology.org/2023.findings-eacl.179/) *— 2023 · Findings of the Association for Computational Linguistics: EACL 2023*
55. [Social-Group-Agnostic Bias Mitigation via the Stereotype Content Model](https://aclanthology.org/2023.acl-long.227/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
56. [Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity](https://arxiv.org/abs/2310.07521) *— 2023 · arXiv:2310.07521*
57. [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)*
58. [TADA : Task Agnostic Dialect Adapters for English](https://aclanthology.org/2023.findings-acl.51/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
59. [TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining](https://aclanthology.org/2023.argmining-1.14/) *— 2023 · Proceedings of the 10th Workshop on Argument Mining*
60. [Taxonomy of Problems in Lexical Semantics](https://aclanthology.org/2023.findings-acl.623/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
61. [Teacher Perception of Automatically Extracted Grammar Concepts for L2 Language Learning](https://aclanthology.org/2023.findings-emnlp.246/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
62. [Text Augmented Spatial Aware Zero-shot Referring Image Segmentation](https://aclanthology.org/2023.findings-emnlp.73/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
63. [The BLA Benchmark: Investigating Basic Language Abilities of Pre-Trained Multimodal Models](https://aclanthology.org/2023.emnlp-main.356/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
64. [The Life Cycle of Knowledge in Big Language Models: A Survey](https://arxiv.org/abs/2303.07616) *— 2023 · arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024*
65. [The Role of Semantic Parsing in Understanding Procedural Text](https://aclanthology.org/2023.findings-eacl.137/) *— 2023 · Findings of the Association for Computational Linguistics: EACL 2023*
66. [The Trickle-down Impact of Reward (In-)consistency on RLHF](https://arxiv.org/abs/2309.16155) *— 2023 · arXiv:2309.16155*
67. [The language of prompting: What linguistic properties make a prompt successful?](https://aclanthology.org/2023.findings-emnlp.618/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
68. [To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion](https://aclanthology.org/2023.acl-long.349/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
69. [Towards Concept-Aware Large Language Models](https://aclanthology.org/2023.findings-emnlp.877/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
70. [Towards Fewer Hallucinations in Knowledge-Grounded Dialogue Generation via Augmentative and Contrastive Knowledge-Dialogue](https://aclanthology.org/2023.acl-short.148/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
71. [Traitement quantique des langues : état de l''art Quantum Natural Language Processing : a review](https://aclanthology.org/2023.tal-1.1/) *— 2023*
72. [Understanding Finetuning for Factual Knowledge Extraction from Language Models](https://arxiv.org/abs/2301.11293) *— 2023 · arXiv:2301.11293*
73. [VISTA: Visual-Textual Knowledge Graph Representation Learning](https://aclanthology.org/2023.findings-emnlp.488/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
74. [Vector-Quantized Prompt Learning for Paraphrase Generation](https://aclanthology.org/2023.findings-emnlp.893/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
75. [ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation](https://aclanthology.org/2023.emnlp-main.824/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
76. [Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information](https://aclanthology.org/2023.acl-long.88/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transport](https://aclanthology.org/2023.findings-acl.864/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
78. [What the DAAM: Interpreting Stable Diffusion Using Cross Attention](https://aclanthology.org/2023.acl-long.310/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
79. [WinoDict: Probing language models for in-context word acquisition](https://aclanthology.org/2023.eacl-main.7/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
80. [Word sense extension](https://aclanthology.org/2023.acl-long.184/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
81. [XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE](https://aclanthology.org/2023.acl-short.135/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
82. [Zero-shot Approach to Overcome Perturbation Sensitivity of Prompts](https://aclanthology.org/2023.acl-long.313/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
83. [``Geen makkie'''': Interpretable Classification and Simplification of Dutch Text Complexity](https://aclanthology.org/2023.bea-1.42/) *— 2023 · Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)*
84. [事前学習済み言語モデルの知識に基づく演繹推論能力の調査](https://www.anlp.jp/proceedings/annual_meeting/2023/#B3-1) *— 2023 · 言語処理学会 第29回年次大会 発表論文集 (NLP2023)*
85. [基于动态常识推理与多维语义特征的幽默识别(Humor Recognition based on Dynamically Commonsense Reasoning and Multi-Dimensional Semantic Features)](https://aclanthology.org/2023.ccl-1.29/) *— 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics*
86. [基于预训练语言模型的端到端概念体系构建方法(End to End Taxonomy Construction Method with Pretrained Language Model)](https://aclanthology.org/2023.ccl-1.49/) *— 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics*
87. [融合Synonyms 词库的专利语义相似度计算研究(Patent Semantic Similarity Calculation by Fusing Synonyms Database)](https://aclanthology.org/2023.ccl-1.30/) *— 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics*
88. [A Neural Machine Translation Approach to Translate Text to Pictographs in a Medical Speech Translation System - The BabelDr Use Case](https://aclanthology.org/2022.amta-research.19/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
89. [A Rationale-Centric Framework for Human-in-the-loop Machine Learning](https://aclanthology.org/2022.acl-long.481/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
90. [A Unified Framework for Pun Generation with Humor Principles](https://aclanthology.org/2022.findings-emnlp.237/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
91. [A large and evolving cognate database](https://link.springer.com/article/10.1007/s10579-021-09544-6) *— 2022 · Language Resources and Evaluation 56: 165–189 (2022)*
92. [ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics](https://md.mova.elamur.ai/free/en/docs/papers/amrhein-2022-aces-translation-accuracy-challenge-sets/) *— our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
93. [Analyzing Encoded Concepts in Transformer Language Models](https://aclanthology.org/2022.naacl-main.225/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
94. [Better Language Model with Hypernym Class Prediction](https://aclanthology.org/2022.acl-long.96/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
95. [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*
96. [Building a Multilingual Taxonomy of Olfactory Terms with Timestamps](https://aclanthology.org/2022.lrec-1.429/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
97. [CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language Model](https://aclanthology.org/2022.findings-emnlp.429/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
98. [CILS at TSAR-2022 Shared Task: Investigating the Applicability of Lexical Substitution Methods for Lexical Simplification](https://aclanthology.org/2022.tsar-1.21/) *— 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)*
99. [CILex: An Investigation of Context Information for Lexical Substitution Methods](https://aclanthology.org/2022.coling-1.362/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
100. [Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation](https://arxiv.org/abs/2203.15319) *— 2022 · arXiv:2203.15319*

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