---
title: "Li Dong — papers"
description: "Li Dong: 12 papers in the Elamur Research library (2014–2024) — our summary of each, its ideas, references and who cites it."
canonical: "https://research.elamur.ai/free/en/authors/li-dong/"
---
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# Li Dong

12 papers on this site (2014–2024)

[OpenAlex](https://openalex.org/A5101751776) · [ORCID](https://orcid.org/0000-0003-2036-1009) · h-index 28 · 102 works · 7585 citations (openalex-snapshot, 2026-10-14)

Profile data from OpenAlex; authors with the same name are not always told apart.

- [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/) — Daijun Ding, Li Dong, Zhichao Huang, et al. · 2024
- [Kosmos-2: Grounding Multimodal Large Language Models to the World](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/) — Zhiliang Peng, Wenhui Wang, Li Dong, et al. · 2023
- [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/) — Shaohan Huang, Li Dong, Wenhui Wang, et al. · 2023
- [MiniLLM: On-Policy Distillation of Large Language Models](https://md.research.elamur.ai/free/en/papers/gu-2023-minillm-policy-distillation-large-language/) — Yuxian Gu, Li Dong, Furu Wei, et al. · 2023
- [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/) — Damai Dai, Yutao Sun, Li Dong, et al. · 2023
- [InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/) — Zewen Chi, Li Dong, Furu Wei, et al. · 2020
- [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/) — Xiujun Li, Xi Yin, Chunyuan Li, et al. · 2020
- [UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/) — Hangbo Bao, Li Dong, Furu Wei, et al. · 2020
- [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/) — Li Dong, Nan Yang, Wenhui Wang, et al. · 2019
- [Learning to Paraphrase for Question Answering](https://md.research.elamur.ai/free/en/papers/dong-2017-learning-paraphrase-question-answering/) — Li Dong, Jonathan Mallinson, Siva Reddy, et al. · 2017
- [Long Short-Term Memory-Networks for Machine Reading](https://md.research.elamur.ai/free/en/papers/cheng-2016-long-short-term-memory-networks/) — Jianpeng Cheng, Li Dong, Mirella Lapata · 2016
- [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/) — Li Dong, Furu Wei, Chuanqi Tan, et al. · 2014