24 results on '"Zun Wang"'
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2. Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel.
3. SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts.
4. DreamRunner: Fine-Grained Storytelling Video Generation with Retrieval-Augmented Motion Adaptation.
5. Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates.
6. FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields.
7. Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models.
8. NavGPT-2: Unleashing Navigational Reasoning Capability for Large Vision-Language Models.
9. Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey.
10. Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models.
11. SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning.
12. Self-Consistency Training for Hamiltonian Prediction.
13. InternVideo2: Scaling Video Foundation Models for Multimodal Video Understanding.
14. Does AI for science need another ImageNet Or totally different benchmarks? A case study of machine learning force fields.
15. ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments.
16. MVBench: A Comprehensive Multi-modal Video Understanding Benchmark.
17. Scaling Data Generation in Vision-and-Language Navigation.
18. InternVideo: General Video Foundation Models via Generative and Discriminative Learning.
19. InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challenges.
20. 1st Place Solutions for RxR-Habitat Vision-and-Language Navigation Competition (CVPR 2022).
21. Bridging the Gap Between Learning in Discrete and Continuous Environments for Vision-and-Language Navigation.
22. An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022.
23. Heterogeneous relational message passing networks for molecular dynamics simulations.
24. Symmetry-adapted graph neural networks for constructing molecular dynamics force fields.
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