🔗 Who cites «Identifying and Controlling Important Neurons in Neural Machine Translation»

91 papers of our library cite it (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · ← back to «Identifying and Controlling Important Neurons in Neural Machine Translation»

1. Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be PrunedAnnual Meeting of the Association for Computational Linguistics (ACL)Elena Voita, David Talbot, Fedor Moiseev, et al.2019 · 1,535 citations
2. Explainability for Large Language Models: A SurveyACM Transactions on Intelligent Systems and TechnologyHaiyan Zhao, Hanjie Chen, Fan Yang, et al.2023 · 790 citations
3. Analysis Methods in Neural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Yonatan Belinkov, James Glass2019 · 740 citations
4. A Multiscale Visualization of Attention in the Transformer ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Jesse Vig2019 · 716 citations
5. Probing Classifiers: Promises, Shortcomings, and AdvancesComputational LinguisticsYonatan Belinkov2022 · 529 citations
6. Information-Theoretic Probing with Minimum Description LengthConference on Empirical Methods in Natural Language Processing (EMNLP)Elena Voita, Ivan Titov2020 · 345 citations
7. xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
8. The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling ObjectivesConference on Empirical Methods in Natural Language Processing (EMNLP)Elena Voita, Rico Sennrich, Ivan Titov2019 · 225 citations
9. Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 197 citations
10. Investigating Multilingual NMT Representations at ScaleConference on Empirical Methods in Natural Language Processing (EMNLP)Sneha Kudugunta, Ankur Bapna, Isaac Caswell, et al.2019 · 176 citations
11. Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyi Tang, Wenyang Luo, Haoyang Huang, et al.2024 · 156 citations
12. How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language modelConference on Neural Information Processing Systems (NeurIPS)Michael Hanna, Ollie Liu, Alexandre Variengien2023 · 151 citations
13. Finding Neurons in a Haystack: Case Studies with Sparse ProbingarXiv:2305.01610Wes Gurnee, Neel Nanda, Matthew Pauly, et al.2023 · 123 citations
14. LSTM Networks Can Perform Dynamic CountingProceedings of the Workshop on Deep Learning and Formal Languages: Building BridgesMirac Suzgun, Yonatan Belinkov, Stuart Shieber, et al.2019 · 89 citations
15. Finding Skill Neurons in Pre-trained Transformer-based Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaozhi Wang, Kaiyue Wen, Zhengyan Zhang, et al.2022 · 85 citations
16. Neuron-level Interpretation of Deep NLP Models: A SurveyTransactions of the Association for Computational Linguistics (TACL)Hassan Sajjad, Nadir Durrani, Fahim Dalvi2022 · 85 citations
17. Wider and Deeper LLM Networks are Fairer LLM EvaluatorsarXiv:2308.01862Xinghua Zhang, Bowen Yu, Haiyang Yu, et al.2023 · 75 citations
18. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
19. On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific NeuronsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Takeshi Kojima, Itsuki Okimura, Yusuke Iwasawa, et al.2024 · 65 citations
20. Information Flow Routes: Automatically Interpreting Language Models at ScaleConference on Empirical Methods in Natural Language Processing (EMNLP)Javier Ferrando, Elena Voita2024 · 43 citations
21. Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language ModelBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPAbhijith Chintam, Rahel Beloch, Willem Zuidema, et al.2023 · 19 citations
22. Enhancing Automated Interpretability with Output-Centric Feature DescriptionsAnnual Meeting of the Association for Computational Linguistics (ACL)Yoav Gur-Arieh, Roy Mayan, Chen Agassy, et al.2025 · 13 citations
23. SAEs Are Good for Steering – If You Select the Right FeaturesConference on Empirical Methods in Natural Language Processing (EMNLP)Dana Arad, Aaron Mueller, Yonatan Belinkov2025 · 12 citations
24. Post-hoc analysis of Arabic transformer modelsBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPAhmed Abdelali, Nadir Durrani, Fahim Dalvi, et al.2022 · 8 citations
25. Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward PassesAnnual Meeting of the Association for Computational Linguistics (ACL)Bryan R Christ, Zachary Gottesman, Jonathan Kropko, et al.2025 · 7 citations
26. Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic ParsingComputational LinguisticsJunjie Cao, Zi Lin, Weiwei Sun, et al.2021 · 6 citations
27. Finding Culture-Sensitive Neurons in Vision-Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Xiutian Zhao, Rochelle Choenni, Rohit Saxena, et al.2026 · 2 citations
28. Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiutian Zhao, Björn Schuller, Berrak Sisman2026 · 1 citation

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

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