Ye, Seonghyeon

1. GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
   2025/03/18 by Nvidia Nvidia, NVIDIA, : +80 · 261 citations
   Engineering · Computer Science · #Robotic Locomotion and Control #Robotic Path Planning Algorithms #Reinforcement Learning in Robotics
2. Latent Action Pretraining from Videos
   2024/10/15 by Seonghyeon Ye, Joel Jang, Ye, Seonghyeon +28 · 77 citations
   Computer Science · Engineering · #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Motion and Animation #Human Pose and Action Recognition #Machine Learning (cs.LG) #Robotics (cs.RO) #Video Analysis and Summarization
3. The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
   2023/05/23 by Seungone Kim, Se June Joo, Kim, Seungone +11 · 24 citations
   Computer Science · Materials Science · Medicine · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Healthcare and Education #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Topic Modeling
4. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets
   2023/07/20 by Seonghyeon Ye, Ye, Seonghyeon, Doyoung Kim +15 · 24 citations
   Computer Science · #Topic Modeling #Natural Language Processing Techniques #Text Readability and Simplification
5. Magma: A Foundation Model for Multimodal AI Agents
   2025/02/18 by Jianwei Yang, Reuben Tan, Yang, Jianwei +23 · 56 citations
   Computer Science · #Multi-Agent Systems and Negotiation #Semantic Web and Ontologies
6. Consent in Crisis: The Rapid Decline of the AI Data Commons
   2024/07/20 by Shayne Longpre, Robert Mahari, Longpre, Shayne +104 · 5 voices · 13 citations
   Computer Science · Social Sciences · #Ethics and Social Impacts of AI #Privacy, Security, and Data Protection #Privacy-Preserving Technologies in Data #cs.AI #cs.CL #cs.LG
7. How Do Large Language Models Acquire Factual Knowledge During Pretraining?
   2024/06/17 by Hoyeon Chang, Chang, Hoyeon, Jinho Park +11 · 1 voice · 22 citations
   Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.7 #Topic Modeling #cs.CL
8. DreamGen: Unlocking Generalization in Robot Learning through Video World Models
   2025/05/19 by Joel Jang, Jang, Joel, Seonghyeon Ye +52 · 44 citations
   Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Robotics (cs.RO)
9. The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
   2024/06/09 by Seungone Kim, Kim, Seungone, Juyoung Suk +61 · 21 citations
   Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
10. TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
    2022/04/29 by Jang, Joel, Ye, Seonghyeon, Lee, Changho +5 · 8 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
11. Towards Continual Knowledge Learning of Language Models
    2021/10/07 by Joel Jang, Seonghyeon Ye, Jang, Joel +13 · 7 citations
    Computer Science · #Computation and Language (cs.CL) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Topic Modeling
12. FLARE: Robot Learning with Implicit World Modeling
    2025/05/21 by Ruijie Zheng, Zheng, Ruijie, Jing Wang +39 · 16 citations
    Computer Science · #Reinforcement Learning in Robotics
13. Self-Explore: Enhancing Mathematical Reasoning in Language Models with Fine-grained Rewards
    2024/04/16 by Hyeonbin Hwang, Hwang, Hyeonbin, Doyoung Kim +7 · 7 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
14. Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
    2023/11/14 by Kim, Yujin, Yoon, Jaehong, Ye, Seonghyeon +4 · 4 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
15. Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following
    2023/02/28 by Seonghyeon Ye, Ye, Seonghyeon, Hyeonbin Hwang +9 · 3 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
16. INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval Models
    2024/02/22 by Oh, Hanseok, Lee, Hyunji, Ye, Seonghyeon +4 · 3 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
17. Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts
    2022/09/26 by Joel Jang, Seonghyeon Ye, Jang, Joel +3 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
18. World Simulation with Video Foundation Models for Physical AI
    2025/10/28 by Nvidia Nvidia, NVIDIA, : +170 · 14 citations
    Computer Science · #Multimodal Machine Learning Applications #Generative Adversarial Networks and Image Synthesis #Reinforcement Learning in Robotics
19. Dimensional Emotion Detection from Categorical Emotion
    2019/11/06 by Park, Sungjoon, Kim, Jiseon, Ye, Seonghyeon +3 · 1 citation
    #Audio and Speech Processing (eess.AS) #Computation and Language (cs.CL) #FOS: Computer and information sciences #FOS: Electrical engineering #Sound (cs.SD) #electronic engineering #information engineering
20. Instruction Matters: A Simple yet Effective Task Selection for Optimized Instruction Tuning of Specific Tasks
    2024/04/25 by Lee, Changho, Han, Janghoon, Ye, Seonghyeon +3 · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
21. Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis
    2023/05/24 by Sohee Yang, Jonghyeon Kim, Yang, Sohee +9 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
22. Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft Prompt
    2022/10/06 by Seonghyeon Ye, Ye, Seonghyeon, Joel Jang +7 · 1 citation
    Computer Science · #Topic Modeling #Machine Learning and Data Classification #Machine Learning and Algorithms