🔗 Who cites «A SICK cure for the evaluation of compositional distributional semantic models»

460 papers of our library cite it (of the 140,884 whose bibliographies we read) · 45 with a page here, the most cited first · ← the paper

1. Sentence-BERT: Sentence Embeddings using Siamese BERT-NetworksNils Reimers, Iryna Gurevych2019 · 4,838 citations
2. SimCSE: Simple Contrastive Learning of Sentence EmbeddingsTianyu Gao, Xingcheng Yao, Danqi Chen2021 · 3,921 citations
3. Know What You Don't Know: Unanswerable Questions for SQuADPranav Rajpurkar, Robin Jia, Percy Liang2018 · 3,360 citations
4. AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated PromptsTaylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.2020 · 1,879 citations
5. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,423 citations
6. ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence PairsWenpeng Yin, Hinrich Schütze, Bing Xiang, et al.2016 · 1,048 citations
7. What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic propertiesAlexis Conneau, German Kruszewski, Guillaume Lample, et al.2018 · 1,021 citations
8. AdapterFusion: Non-Destructive Task Composition for Transfer LearningJonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.2020 · 948 citations
9. SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused EvaluationDaniel Cer, Mona Diab, Eneko Agirre, et al.2017 · 907 citations
10. On the Sentence Embeddings from Pre-trained Language ModelsBohan Li, Hao Zhou, Junxian He, et al.2020 · 830 citations
11. Learning Distributed Representations of Sentences from Unlabelled DataFelix Hill, Kyunghyun Cho, Anna Korhonen2016 · 756 citations
12. SentEval: An Evaluation Toolkit for Universal Sentence RepresentationsAlexis Conneau, Douwe Kiela2018 · 739 citations
13. Explain Yourself! Leveraging Language Models for Commonsense ReasoningNazneen Fatema Rajani, Bryan McCann, Caiming Xiong, et al.2019 · 690 citations
14. ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation TransferYuanmeng Yan, Rumei Li, Sirui Wang, et al.2021 · 647 citations
15. e-SNLI: Natural Language Inference with Natural Language ExplanationsOana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, et al.2018 · 612 citations
16. An efficient framework for learning sentence representationsLajanugen Logeswaran, Honglak Lee2018 · 573 citations
17. SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual EntailmentMarco Marelli, Luisa Bentivogli, Marco Baroni, et al.2014 · 520 citations
18. DeCLUTR: Deep Contrastive Learning for Unsupervised Textual RepresentationsJohn Giorgi, Osvald Nitski, Bo Wang, et al.2021 · 513 citations
19. Learning Natural Language Inference with LSTMShuohang Wang, Jing Jiang2016 · 491 citations
20. From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual TransformersAnne Lauscher, Vinit Ravishankar, Ivan Vulić, et al.2020 · 461 citations
21. Emergent: a novel data-set for stance classificationWilliam Ferreira, Andreas Vlachos2016 · 456 citations
22. Dialogue Natural Language InferenceSean Welleck, Jason Weston, Arthur Szlam, et al.2019 · 382 citations
23. AlignScore: Evaluating Factual Consistency with A Unified Alignment FunctionYuheng Zha, Yichi Yang, Ruichen Li, et al.2023 · 280 citations
24. DiffCSE: Difference-based Contrastive Learning for Sentence EmbeddingsYung-Sung Chuang, Rumen Dangovski, Hongyin Luo, et al.2022 · 269 citations
25. How Can We Accelerate Progress Towards Human-like Linguistic Generalization?Tal Linzen2020 · 257 citations
26. Generating Datasets with Pretrained Language ModelsTimo Schick, Hinrich Schutze2021 · 250 citations
27. Self-Guided Contrastive Learning for BERT Sentence RepresentationsTaeuk Kim, Kang Min Yoo, Sang-goo Lee2021 · 234 citations
28. Probing for semantic evidence of composition by means of simple classification tasksAllyson Ettinger, Ahmed Elgohary, Philip Resnik2016 · 217 citations
29. An Unsupervised Sentence Embedding Method by Mutual Information MaximizationYan Zhang, Ruidan He, Zuozhu Liu, et al.2020 · 213 citations
30. One Embedder, Any Task: Instruction-Finetuned Text EmbeddingsHongjin Su, Weijia Shi, Jungo Kasai, et al.2022 · 191 citations
31. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesShane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 134 citations
32. Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual EntailmentMasatoshi Tsuchiya2018 · 125 citations
33. EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language InferenceAbhilasha Ravichander, Aakanksha Naik, Carolyn Rose, et al.2019 · 122 citations
34. Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language InferenceYonatan Belinkov, Adam Poliak, Stuart Shieber, et al.2019 · 121 citations
35. Inference is Everything: Recasting Semantic Resources into a Unified Evaluation FrameworkAaron Steven White, Pushpendre Rastogi, Kevin Duh, et al.2017 · 110 citations
36. End-to-End Bias Mitigation by Modelling Biases in CorporaRabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson2020 · 107 citations
37. Investigating Reasons for Disagreement in Natural Language InferenceNan-Jiang Jiang, Marie-Catherine de Marneffe2022 · 104 citations
38. JGLUE: Japanese General Language Understanding EvaluationKentaro Kurihara, Daisuke Kawahara, Tomohide Shibata2022 · 90 citations
39. Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph SimilarityJuri Opitz, Angel Daza, Anette Frank2021 · 47 citations
40. The First Shared Task on Discourse Representation Structure ParsingLasha Abzianidze, Rik van Noord, Hessel Haagsma, et al.2019 · 16 citations
41. Combining Event Semantics and Degree Semantics for Natural Language InferenceIzumi Haruta, Koji Mineshima, Daisuke Bekki2020 · 12 citations
42. What can we learn from Semantic Tagging?Mostafa Abdou, Artur Kulmizev, Vinit Ravishankar, et al.2018 · 11 citations
43. Challenging the Transformer-based models with a Classical Arabic dataset: Quran and HadithShatha Altammami, Eric Atwell2022 · 6 citations
44. Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent EncodersYuwei Zhang, Siffi Singh, Sailik Sengupta, et al.2024 · 4 citations
45. Can generative AI recognise textual entailment? (生成 AI は含意関係認識ができるのか)荒沢康平, 狩野芳伸2024

415 more papers of our library cite it; they have no page here yet.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/marelli-2014-sick-cure-evaluation-compositional-distributional/cited-by/