🧑‍🔬 Shuming Shi — all works

40 works · ← Shuming Shi

1. Encouraging Divergent Thinking in Large Language Models through Multi-Agent DebateConference on Empirical Methods in Natural Language Processing (EMNLP)Tian Liang, Zhiwei He, Wenxiang Jiao, et al.2023 · 651 citations
2. Is ChatGPT A Good Translator? Yes With GPT-4 As The EnginearXiv:2301.08745Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, et al.2023 · 632 citations
3. Deep Neural Solver for Math Word Problems ↗Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yetYan Wang, Xiaojiang Liu, Shuming Shi2017 · 488 citations
4. Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word EmbeddingsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yan Song, Shuming Shi, Jing Li, et al.2018 · 443 citations
5. Document-Level Machine Translation with Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.2023 · 297 citations
6. Automatically Solving Number Word Problems by Semantic Parsing and Reasoning ↗Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yetShuming Shi et al.2015 · 267 citations
7. Exploring Human-Like Translation Strategy with Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Zhiwei He, Tian Liang, Wenxiang Jiao, et al.2024 · 207 citations
8. How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation ↗Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDanqing Huang et al.2016 · 203 citations
9. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 168 citations
10. Learning Fine-Grained Expressions to Solve Math Word Problems ↗Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yetDanqing Huang et al.2017 · 131 citations
11. MAGE: Machine-generated Text Detection in the WildAnnual Meeting of the Association for Computational Linguistics (ACL)Yafu Li, Qintong Li, Leyang Cui, et al.2024 · 129 citations
12. On the Inference Calibration of Neural Machine Translation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetShuo Wang et al.2020 · 124 citations
13. On the Word Alignment from Neural Machine Translation ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetXintong Li et al.2019 · 121 citations
14. Exploiting Deep Representations for Neural Machine Translation ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetZi-Yi Dou et al.2018 · 117 citations
15. Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical StudyFindings of the Association for Computational LinguisticsYi Chen, Rui Wang, Haiyun Jiang, et al.2023 · 113 citations
16. Topic-Aware Neural Keyphrase Generation for Social Media Language ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetYue Wang et al.2019 · 110 citations
17. Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory ↗Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · no summary yetDeng Cai et al.2019 · 101 citations
18. Self-Attention with Structural Position Representations ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetXing Wang et al.2019 · 90 citations
19. Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetDeng Cai et al.2019 · 86 citations
20. Generating Classical Chinese Poems via Conditional Variational Autoencoder and Adversarial Training ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetJuntao Li et al.2018 · 86 citations
21. Knowledge Fusion of Large Language Models ↗arXiv:2401.10491 · no summary yetFanqi Wan et al.2024 · 82 citations
22. Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text IntegrationarXiv:2306.09093Chenyang Lyu, Minghao Wu, Longyue Wang, et al.2023 · 75 citations
23. Semi-supervised Text Style Transfer: Cross Projection in Latent Space ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetMingyue Shang et al.2019 · 72 citations
24. On the Evaluation Metrics for Paraphrase Generation ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetLingfeng Shen et al.2022 · 66 citations
25. Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Jianhui Pang, Fanghua Ye, Derek Fai Wong, et al.2025 · 65 citations
26. DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models ↗arXiv:2503.04472 · no summary yetYi Shen et al.2025 · 57 citations
27. Neural Machine Translation with Adequacy-Oriented Learning ↗arXiv:1811.08541 · no summary yetXiang Kong et al.2018 · 45 citations
28. One Model to Learn Both: Zero Pronoun Prediction and TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Longyue Wang, Zhaopeng Tu, Xing Wang, et al.2019 · 41 citations
29. Evaluating Explanation Methods for Neural Machine Translation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetJierui Li et al.2020 · 38 citations
30. Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetZhiwei He et al.2024 · 30 citations
31. Benchmarking and Improving Long-Text Translation with Large Language Models ↗Findings of the Association for Computational Linguistics: ACL 2024 · no summary yetLongyue Wang et al.2024 · 26 citations
32. Language Style Transfer from Sentences with Arbitrary Unknown Styles ↗arXiv:1808.04071 · no summary yetYanpeng Zhao et al.2018 · 20 citations
33. GuoFeng: A Benchmark for Zero Pronoun Recovery and TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Mingzhou Xu, Longyue Wang, Derek F. Wong, et al.2022 · 18 citations
34. Spotting AI's Touch: Identifying LLM-Paraphrased Spans in Text ↗Findings of the Association for Computational Linguistics: ACL 2024 · no summary yetYafu Li et al.2024 · 12 citations
35. MCPG: A Flexible Multi-Level Controllable Framework for Unsupervised Paraphrase Generation ↗Findings of the Association for Computational Linguistics: EMNLP 2022 · no summary yetYi Chen et al.2022 · 10 citations
36. Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics ↗Findings of the Association for Computational Linguistics: ACL 2022 · no summary yetJiannan Xiang et al.2022 · 5 citations
37. Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models ↗arXiv:2004.13270 · no summary yetShilin He et al.2020 · 2 citations
38. Mixture of Heterogeneous Grouped Experts for Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhicheng Ma, Xiang Liu, Zhaoxiang Liu, et al.2026
39. IMTLab: An Open-Source Platform for Building, Evaluating, and Diagnosing Interactive Machine Translation Systems ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetXu Huang et al.2023
40. QuaSE: Accurate Text Style Transfer under Quantifiable Guidance ↗arXiv:1804.07007 · no summary yetYi Liao et al.2018

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