---
title: "Li Dong — all works — Elamur Research"
description: "All 29 works of Li Dong 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/li-dong/works/"
---
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# Li Dong — all works

29 works · [← Li Dong](https://md.research.elamur.ai/free/en/authors/li-dong/)

1. **[Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xiujun Li, Xi Yin, Chunyuan Li, et al.*2020 · 1,877 citations*
2. [**Unified Language Model Pre-training for Natural Language Understanding and Generation arXiv:1905.03197**Li Dong, Nan Yang, Wenhui Wang, et al.*2019 · 1,422 citations*](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/)
3. **[Long Short-Term Memory-Networks for Machine Reading](https://md.research.elamur.ai/free/en/papers/cheng-2016-long-short-term-memory-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jianpeng Cheng, Li Dong, Mirella Lapata*2016 · 1,313 citations*
4. **[Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification](https://md.research.elamur.ai/free/en/papers/dong-2014-adaptive-recursive-neural-network-target/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Dong, Furu Wei, Chuanqi Tan, et al.*2014 · 1,217 citations*
5. **[Language to Logical Form with Neural Attention](https://md.research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Dong, Mirella Lapata*2016 · 955 citations*
6. **[Knowledge Neurons in Pretrained Transformers ↗](https://aclanthology.org/2022.acl-long.581/) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Damai Dai et al.*2022 · 568 citations*
7. **[Coarse-to-Fine Decoding for Neural Semantic Parsing ↗](https://aclanthology.org/P18-1068/) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Li Dong, Mirella Lapata*2018 · 518 citations*
8. [**UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training arXiv:2002.12804**Hangbo Bao, Li Dong, Furu Wei, et al.*2020 · 395 citations*](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/)
9. **[Language Is Not All You Need: Aligning Perception with Language Models](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 330 citations*
10. **[MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers ↗](https://aclanthology.org/2021.findings-acl.188/) Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 · no summary yet**Wenhui Wang et al.*2021 · 311 citations*
11. [**Kosmos-2: Grounding Multimodal Large Language Models to the World arXiv:2306.14824**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
12. **[Learning to Paraphrase for Question Answering](https://md.research.elamur.ai/free/en/papers/dong-2017-learning-paraphrase-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Li Dong, Jonathan Mallinson, Siva Reddy, et al.*2017 · 286 citations*
13. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training arXiv:2007.07834**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 275 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
14. [**Retentive Network: A Successor to Transformer for Large Language Models arXiv:2307.08621**Yutao Sun, Li Dong, Shaohan Huang, et al.*2023 · 265 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-retentive-network-successor-transformer-large/)
15. **[Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Damai Dai, Yutao Sun, Li Dong, et al.*2023 · 257 citations*
16. **[InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training ↗](https://aclanthology.org/2021.naacl-main.280/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Zewen Chi et al.*2021 · 256 citations*
17. **[Self-Attention Attribution: Interpreting Information Interactions Inside Transformer ↗](https://doi.org/10.1609/aaai.v35i14.17533) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Yaru Hao et al.*2021 · 243 citations*
18. **[Visualizing and Understanding the Effectiveness of BERT](https://md.research.elamur.ai/free/en/papers/hao-2019-visualizing-understanding-effectiveness-bert/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaru Hao, Li Dong, Furu Wei, et al.*2019 · 222 citations*
19. **[Data-to-text Generation with Entity Modeling](https://md.research.elamur.ai/free/en/papers/puduppully-2019-data-text-generation-entity-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ratish Puduppully, Li Dong, Mirella Lapata*2019 · 181 citations*
20. [**MiniLLM: On-Policy Distillation of Large Language Models arXiv:2306.08543**Yuxian Gu, Li Dong, Furu Wei, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/)
21. **[Controllable Natural Language Generation with Contrastive Prefixes](https://md.research.elamur.ai/free/en/papers/qian-2022-controllable-natural-language-generation-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Qian, Li Dong, Yelong Shen, et al.*2022 · 130 citations*
22. **[XLM-E: Cross-lingual Language Model Pre-training via ELECTRA](https://md.research.elamur.ai/free/en/papers/chi-2022-xlm-e-cross-lingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zewen Chi, Shaohan Huang, Li Dong, et al.*2022 · 127 citations*
23. **[A Length-Extrapolatable Transformer](https://md.research.elamur.ai/free/en/papers/sun-2023-length-extrapolatable-transformer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutao Sun, Li Dong, Barun Patra, et al.*2023 · 118 citations*
24. **[Confidence Modeling for Neural Semantic Parsing ↗](https://aclanthology.org/P18-1069/) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Li Dong, Chris Quirk, Mirella Lapata*2018 · 105 citations*
25. **[mT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs ↗](https://aclanthology.org/2021.emnlp-main.125/) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yet**Zewen Chi et al.*2021 · 91 citations*
26. **[Language Models as Inductive Reasoners](https://md.research.elamur.ai/free/en/papers/yang-2024-language-models-as-inductive-reasoners/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zonglin Yang, Li Dong, Xinya Du, et al.*2024 · 70 citations*
27. **[EDDA: An Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection](https://md.research.elamur.ai/free/en/papers/ding-2024-edda-encoder-decoder-data-augmentation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daijun Ding, Li Dong, Zhichao Huang, et al.*2024 · 9 citations*
28. **[Rectified Sparse Attention for Efficient Long-Sequence Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-rectified-sparse-attention-efficient-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Sun, Tianzhu Ye, Li Dong, et al.*2026 · 1 citation*
29. **[Towards Stable and Effective Reinforcement Learning for Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-effective-reinforcement-learning-mixture/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Di Zhang, Xun Wu, Shaohan Huang, et al.*2026 · 1 citation*