🧑‍🔬 Yang Chen

🏛️ Affiliations

🏛️Chinese Academy of SciencesBeijing · China2013–2026 · 134 paperscurrent🔬Chongqing Institute of Green and Intelligent TechnologyChongqing · China2016–2026 · 133 paperscurrent🔬Institute of Earth EnvironmentXi'an · China2013–2026 · 11 paperscurrent🔬Hubei Three Gorges LaboratoryYichang · China2026 · 1 papercurrent🎓Chongqing Academy of Science and TechnologyChongqing · China2016–2025 · 6 papers🎓University of Chinese Academy of SciencesBeijing · China2020–2024 · 4 papers🎓Lanzhou UniversityLanzhou · China2021–2023 · 4 papers🎓Sichuan UniversityChengdu · China2025 · 3 papers🎓Wuhan University of Science and TechnologyWuhan · China2012–2025 · 3 papers🔬State Key Laboratory of Loess and Quaternary GeologyXi'an2019 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 45 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions? (2023 · 111 citations)
   The paper asks whether current pre-trained vision-language models can handle questions about an image that need specific factual knowledge not visible in the picture, such as when a pictured church was built.
2. An Empirical Study of Pre-trained Transformers for Arabic Information Extraction (2020 · 107 citations)
   Multilingual encoders such as mBERT and XLM-RoBERTa can be fine-tuned on English labels and then applied to Arabic.
3. AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy (2025 · 21 citations)
   The paper asks how supervised fine-tuning (SFT) and reinforcement learning (RL) interact when post-training a small LLM for math and code reasoning.
4. Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation (2026 · 16 citations)
   Post-training a single LLM across many reasoning and agentic domains is hard. Mixing diverse RL environments can destabilize training, and gains in one area often erode others. Nemotron-Cascade 2 extends NVIDIA's earlier Cascade RL approach, which trains domain by domain in sequence, to address this. The base model…
5. Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models (2025 · 7 citations)
   Extending large language models to very long contexts is difficult for three reasons. Natural documents of 32K–128K tokens are scarce. Upsampling long data shifts the training distribution and can hurt short-context skills. Attention over long sequences is also expensive. The authors propose Untie the Knots (UtK), an…

🤝 Co-authors here

12 of 22 co-authors with a page, the most papers together first.

• Alan Ritter ×2
• Chankyu Lee ×2
• Zhuolin Yang ×2
• Zihan Liu ×2
• Boxin Wang
• Bryan Catanzaro
• Da Zheng
• Dongfu Jiang
• Hexiang Hu
• Junfeng Tian
• Ming-Wei Chang
• Mohammad Shoeybi

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference on Empirical Methods in Natural Language Processing (EMNLP) ×2: EMNLP 2023, EMNLP 2020
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2025

🔗 Cited by

Papers of our library cite their works 138 times (of the 149,439 papers whose bibliographies we read); 47 citing papers with a page here →.

Updated 30 October 2026

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