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Shuohang Wang — all works

29 works · ← Shuohang Wang

  1. Machine Comprehension Using Match-LSTM and Answer PointerarXiv:1608.07905Shuohang Wang, Jing Jiang2016 · 541 citations
  2. An Empirical Study of Training End-to-End Vision-and-Language Transformers ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetZi-Yi Dou et al.2022 · 397 citations
  3. Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsarXiv:2209.10063Wenhao Yu, Dan Iter, Shuohang Wang, et al.2022 · 281 citations
  4. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  5. Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetYi Tay et al.2019 · 133 citations
  6. A Co-Matching Model for Multi-choice Reading Comprehension ↗Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetShuohang Wang et al.2018 · 127 citations
  7. Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShuohang Wang et al.2022 · 125 citations
  8. Contrastive Distillation on Intermediate Representations for Language Model Compression ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetSiqi Sun et al.2020 · 103 citations
  9. Small Models are Valuable Plug-ins for Large Language Models ↗Findings of the Association for Computational Linguistics: ACL 2024 · no summary yetCanwen Xu et al.2024 · 96 citations
  10. LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetSiqi Sun et al.2021 · 96 citations
  11. Reinforcement Learning for Reasoning in Large Language Models with One Training Example ↗arXiv:2504.20571 · no summary yetYiping Wang et al.2025 · 87 citations
  12. Dict-BERT: Enhancing Language Model Pre-training with Dictionary ↗Findings of the Association for Computational Linguistics: ACL 2022 · no summary yetWenhao Yu et al.2022 · 85 citations
  13. T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetBoxin Wang et al.2020 · 82 citations
  14. Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetYi Tay et al.2019 · 76 citations
  15. Knowledge Base Question Answering With a Matching-Aggregation Model and Question-Specific Contextual Relations ↗IEEE/ACM Transactions on Audio Speech and Language Processing · no summary yetYunshi Lan, Shuohang Wang, Jing Jiang2019 · 58 citations
  16. Compositional De-Attention Networks ↗neural information processing systems · no summary yetYi Tay et al.2019 · 18 citations
  17. On Orthogonality Constraints for Transformers ↗Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers) · no summary yetAston Zhang et al.2021 · 11 citations
  18. GRIN: GRadient-INformed MoEarXiv:2409.12136Liyuan Liu, Young Jin Kim, Shuohang Wang, et al.2024 · 7 citations
  19. MLP Architectures for Vision-and-Language Modeling: An Empirical Study ↗arXiv (Cornell University) · no summary yetYixin Nie et al.2021 · 6 citations
  20. Multi-Level Head-Wise Match and Aggregation in Transformer for Textual Sequence Matching ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetShuohang Wang et al.2020 · 6 citations
  21. ParaTag: A Dataset of Paraphrase Tagging for Fine-Grained Labels, NLG Evaluation, and Data Augmentation ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetShuohang Wang et al.2022 · 5 citations

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