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Ke M. Tran

The Importance of Being Recurrent for Modeling Hierarchical Structure
2018 · Ke Tran, Arianna Bisazza, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 163
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Recurrent Memory Networks for Language Modeling
2016 · Ke Tran, Arianna Bisazza, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 86
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Unsupervised Neural Hidden Markov Models
2016 · Ke M. Tran, Yonatan Bisk, et al. · Workshop on Structured Prediction for NLP (SPNLP) · 55
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A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs
2016 · Kristina Toutanova, Chris Brockett, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 41
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Making Readability Indices Readable
2012 · Sara Tonelli, Ke Tran Manh, et al. · 35
Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations
2019 · Ke Tran, Arianna Bisazza · Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo) · 28
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From English To Foreign Languages: Transferring Pre-trained Language Models
2020 · Tran, Ke · arXiv (Cornell University) · 22
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Inducing Grammars with and for Neural Machine Translation
2018 · Yonatan Bisk, Ke Tran · 15
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Word Translation Prediction for Morphologically Rich Languages with Bilingual Neural Networks
2014 · Ke M. Tran, Arianna Bisazza, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 15
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Recurrent Memory Network for Language Modeling.
2016 · Ke Tran, Arianna Bisazza, et al. · arXiv (Cornell University) · 14
Sockeye 3: Fast Neural Machine Translation with PyTorch
2022 · Hieber, Felix, Denkowski, Michael, et al. · arXiv (Cornell University) · 11
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Inducing Grammars with and for Neural Machine Translation
2018 · Tran, Ke, Bisk, Yonatan · arXiv (Cornell University) · 6
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The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities
2024 · David Stap, Eva Hasler, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 5
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Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation
2021 · Eva Hasler, Tobias Domhan, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 4
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Generating Synthetic Data for Task-Oriented Semantic Parsing with Hierarchical Representations
2020 · Ke Tran, Ming Tan · Workshop on Structured Prediction for NLP (SPNLP) · 4
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The Amazon Nova Family of Models: Technical Report and Model Card
2025 · AGI, Amazon, Langford, Aaron, et al. · arXiv (Cornell University) · 2
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A Hybrid Approach to Cross-lingual Product Review Summarization
2022 · Saleh Soltan, Victor Soto, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2
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Examining Cooperation in Visual Dialog Models
2017 · Mironenco, Mircea, Kianfar, Dana, et al. · arXiv (Cornell University) · 2
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A distributed inflection model for translating into morphologically rich languages
2015 · Ke Tran, Arianna Bisazza, et al. · UvA-DARE (University of Amsterdam) · 2
The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation
2022 · Tobias Domhan, Eva Hasler, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 1
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What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation
2026 · Association for Computational Linguistics 2026, Byrne, Bill, et al. · Underline Science Inc.
What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation
2026 · Tan, Shaomu, Zhu, Dawei, et al. · arXiv (Cornell University)
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What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation
2026 · Shaomu Tan, Dawei Zhu, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation
2022 · Domhan, Tobias, Hasler, Eva, et al. · arXiv (Cornell University)
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Works count: 29
Citation count: 513
H-index: 11
I10-index: 11
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