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Min-Yen Kan — all works

29 works · ← Min-Yen Kan

  1. A PDTB-Styled End-to-End Discourse ParserNatural Language EngineeringZiheng Lin, Hwee Tou Ng, Min-Yen Kan2010 · 332 citations
  2. Paraphrase Recognition via Dissimilarity Significance Classification ↗Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing · no summary yetLong Qiu, Min-Yen Kan, Tat-Seng Chua2006 · 134 citations
  3. Re-examining the Role of Schema Linking in Text-to-SQL ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetWenqiang Lei et al.2020 · 121 citations
  4. Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetYixin Cao et al.2020 · 105 citations
  5. Context-aware Image Tweet Modelling and Recommendation ↗ACM International Conference on Multimedia (ACM MM) · no summary yetTao Chen, Xiangnan He, Min‐Yen Kan2016 · 84 citations
  6. Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetSamson Tan et al.2020 · 57 citations
  7. Topological Ordering of Function Words in Hierarchical Phrase-based TranslationHendra Setiawan, Min-Yen Kan, Haizhou Li, et al.Machine translation · 31 citations
  8. Combining Coherence Models and Machine Translation Evaluation Metrics for Summarization Evaluation ↗Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZiheng Lin et al.2012 · 29 citations
  9. So Different Yet So Alike! Constrained Unsupervised Text Style Transfer ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetAbhinav Ramesh Kashyap et al.2022 · 19 citations
  10. Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm ReasoningarXiv:2311.08385Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.2023 · 12 citations
  11. When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration ↗arXiv (Cornell University) · no summary yetAI Collaboration et al.2026
  12. When Does Mixing Help? Analyzing Query Embedding Interpolation in Multilingual Dense Retrieval ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetTongyao Zhu, Huang Chao Ming, Min-Yen Kan2026

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