---
title: "Shuohang Wang — all works — Elamur Research"
description: "All 29 works of Shuohang Wang in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/shuohang-wang/works/"
---
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# Shuohang Wang — all works

29 works · [← Shuohang Wang](https://md.research.elamur.ai/free/en/authors/shuohang-wang/)

1. **[G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Dan Iter, Yichong Xu, et al.*2023 · 2,000 citations*
2. [**Machine Comprehension Using Match-LSTM and Answer Pointer arXiv:1608.07905**Shuohang Wang, Jing Jiang*2016 · 541 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-machine-comprehension-using-match-lstm/)
3. **[Learning Natural Language Inference with LSTM](https://md.research.elamur.ai/free/en/papers/wang-2016-learning-natural-language-inference-lstm/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shuohang Wang, Jing Jiang*2016 · 499 citations*
4. **[An Empirical Study of Training End-to-End Vision-and-Language Transformers ↗](https://doi.org/10.1109/cvpr52688.2022.01763) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Zi-Yi Dou et al.*2022 · 397 citations*
5. **[Want To Reduce Labeling Cost? GPT-3 Can Help](https://md.research.elamur.ai/free/en/papers/wang-2021-want-reduce-labeling-cost-gpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuohang Wang, Yang Liu, Yichong Xu, et al.*2021 · 300 citations*
6. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators arXiv:2209.10063**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 281 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
7. **[Hierarchical Graph Network for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/fang-2020-hierarchical-graph-network-multi-hop/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuwei Fang, Siqi Sun, Zhe Gan, et al.*2020 · 243 citations*
8. [**Prompting GPT-3 To Be Reliable arXiv:2210.09150**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
9. **[Multi-Fact Correction in Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/dong-2020-multi-fact-correction-abstractive-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yue Dong, Shuohang Wang, Zhe Gan, et al.*2020 · 163 citations*
10. **[Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives ↗](https://aclanthology.org/P19-1486/) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yet**Yi Tay et al.*2019 · 133 citations*
11. **[A Co-Matching Model for Multi-choice Reading Comprehension ↗](https://aclanthology.org/P18-2118/) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yet**Shuohang Wang et al.*2018 · 127 citations*
12. **[Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data ↗](https://aclanthology.org/2022.acl-long.226/) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Shuohang Wang et al.*2022 · 125 citations*
13. **[KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2022-kg-fid-infusing-knowledge-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donghan Yu, Chenguang Zhu, Yuwei Fang, et al.*2022 · 116 citations*
14. **[Contrastive Distillation on Intermediate Representations for Language Model Compression ↗](https://aclanthology.org/2020.emnlp-main.36/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Siqi Sun et al.*2020 · 103 citations*
15. **[Small Models are Valuable Plug-ins for Large Language Models ↗](https://aclanthology.org/2024.findings-acl.18/) Findings of the Association for Computational Linguistics: ACL 2024 · no summary yet**Canwen Xu et al.*2024 · 96 citations*
16. **[LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval ↗](https://aclanthology.org/2021.naacl-main.77/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Siqi Sun et al.*2021 · 96 citations*
17. **[Reinforcement Learning for Reasoning in Large Language Models with One Training Example ↗](https://arxiv.org/abs/2504.20571) arXiv:2504.20571 · no summary yet**Yiping Wang et al.*2025 · 87 citations*
18. **[Dict-BERT: Enhancing Language Model Pre-training with Dictionary ↗](https://aclanthology.org/2022.findings-acl.150/) Findings of the Association for Computational Linguistics: ACL 2022 · no summary yet**Wenhao Yu et al.*2022 · 85 citations*
19. **[T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack ↗](https://aclanthology.org/2020.emnlp-main.495/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Boxin Wang et al.*2020 · 82 citations*
20. **[Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks ↗](https://aclanthology.org/P19-1145/) Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yet**Yi Tay et al.*2019 · 76 citations*
21. **[Knowledge Base Question Answering With a Matching-Aggregation Model and Question-Specific Contextual Relations ↗](https://doi.org/10.1109/taslp.2019.2926125) IEEE/ACM Transactions on Audio Speech and Language Processing · no summary yet**Yunshi Lan, Shuohang Wang, Jing Jiang*2019 · 58 citations*
22. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
23. **[Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space](https://md.research.elamur.ai/free/en/papers/zhang-2025-soft-thinking-unlocking-reasoning-potential/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Zhang, Xuehai He, Weixiang Yan, et al.*2025 · 25 citations*
24. **[Compositional De-Attention Networks ↗](https://openalex.org/W2970288142) neural information processing systems · no summary yet**Yi Tay et al.*2019 · 18 citations*
25. **[On Orthogonality Constraints for Transformers ↗](https://aclanthology.org/2021.acl-short.48/) 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 yet**Aston Zhang et al.*2021 · 11 citations*
26. [**GRIN: GRadient-INformed MoE arXiv:2409.12136**Liyuan Liu, Young Jin Kim, Shuohang Wang, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-grin-gradient-informed-moe/)
27. **[MLP Architectures for Vision-and-Language Modeling: An Empirical Study ↗](https://arxiv.org/abs/2112.04453) arXiv (Cornell University) · no summary yet**Yixin Nie et al.*2021 · 6 citations*
28. **[Multi-Level Head-Wise Match and Aggregation in Transformer for Textual Sequence Matching ↗](https://doi.org/10.1609/aaai.v34i05.6458) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Shuohang Wang et al.*2020 · 6 citations*
29. **[ParaTag: A Dataset of Paraphrase Tagging for Fine-Grained Labels, NLG Evaluation, and Data Augmentation ↗](https://aclanthology.org/2022.emnlp-main.479/) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yet**Shuohang Wang et al.*2022 · 5 citations*