Scholar
Yongyuan Liang
Google Scholar ID: GQToORIAAAAJ
University of Maryland, College Park
Large Language Models
Large Multimodal Models
Reinforcement Learning
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Citations & Impact
All-time
Citations
715
H-index
13
i10-index
14
Publications
20
Co-authors
0
Contact
Email
charlotte9762@gmail.com
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Publications
15 items
Anticipatory Planning for Multimodal AI Agents
2026
Cited
0
Learning Situated Awareness in the Real World
2026
Cited
0
Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation
2026
Cited
0
MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Model for Embodied Task Planning
2025
Cited
0
Lemon: A Unified and Scalable 3D Multimodal Model for Universal Spatial Understanding
2025
Cited
0
TraceGen: World Modeling in 3D Trace Space Enables Learning from Cross-Embodiment Videos
2025
Cited
0
WEAVE: Unleashing and Benchmarking the In-context Interleaved Comprehension and Generation
2025
Cited
0
ROVER: Benchmarking Reciprocal Cross-Modal Reasoning for Omnimodal Generation
2025
Cited
0
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Resume (English only)
Academic Achievements
Multiple papers accepted at top-tier conferences including NeurIPS 2025, CVPR 2025, ICLR 2025, and ICML 2024
Awarded Dean's Fellowship in 2024
Paper 'ACE' selected as a long oral presentation at ICML 2024
Three papers accepted at ICLR 2024, including two spotlights
Leads or contributes to open-source initiatives such as Awesome-Generalist-Agents, Magma, and Make-An-Agent
Notable works include: ROVER (benchmark for multimodal reasoning), LEMON (3D multimodal model), Avocado (multi-objective alignment framework), and TraceVLA (embodied agent policy model)
Background
Research focuses on developing foundation models and intelligent agents
Actively explores both theoretical frameworks and empirical findings, with specific interests in:
- Large Multimodal Models: Unified models for 2D/3D virtual and physical agentic tasks
- Alignment: Human preference alignment and cross-modality alignment in post-training
- Previous research includes Reinforcement Learning, Representations, and Robustness
Co-authors
0 total
Co-authors: 0 (list not available)
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