🧑‍🔬 Chankyu Lee

🏛️ Affiliations

🎓Gangneung–Wonju National UniversityGangneung · South Korea2025–2026 · 3 paperscurrent🎓Purdue University West LafayetteWest Lafayette · United States2018–2025 · 13 papers🏢EuBiologicsChuncheon · South Korea2019–2025 · 6 papers🎓University of FloridaGainesville · United States2020 · 4 papers🎓Chung-Ang UniversitySeoul · South Korea2020–2022 · 3 papers🎓Hanyang UniversitySeoul · South Korea2002–2020 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models (2024 · 222 citations)
   General-purpose text embeddings are used for search, clustering, classification and the retrieval step in RAG systems.
2. ChatQA: Surpassing GPT-4 on Conversational QA and RAG (2024 · 58 citations)
   The paper asks whether open-weight LLMs can match proprietary systems like GPT-4 at answering multi-turn questions grounded in supplied or retrieved documents, including tables, arithmetic, and questions the context cannot answer.
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…

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
2. ChatQA: Surpassing GPT-4 on Conversational QA and RAGConference on Neural Information Processing Systems (NeurIPS)Zihan Liu, Wei Ping, Rajarshi Roy, et al.2024 · 58 citations
3. AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning ↗arXiv:2505.16400 · no summary yetYang Chen et al.2025 · 30 citations
4. AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL SynergyarXiv:2506.13284Zihan Liu, Zhuolin Yang, Yang Chen, et al.2025 · 21 citations
5. Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy DistillationarXiv:2603.19220Zhuolin Yang, Zihan Liu, Yang Chen, et al.2026 · 16 citations

🤝 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

• Bryan Catanzaro ×3
• Mohammad Shoeybi ×3
• Wei Ping ×3
• Zihan Liu ×3
• Rajarshi Roy ×2
• Yang Chen ×2
• Zhuolin Yang ×2
• Boxin Wang
• Dongfu Jiang
• Peng Xu
• Renjie Pi
• Sheng-Chieh Lin

Venues

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

• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2024

🔗 Cited by

Papers of our library cite their works 327 times (of the 149,439 papers whose bibliographies we read); 66 citing papers with a page here →.

Updated 1 November 2026

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