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Zecong Tang

Observed names: Tang Zecong, Tang, Zecong
OpenAlex ID: A5121873825
Drive-KD: Multi-Teacher Distillation for VLMs in Autonomous Driving
2026 · Lian, Weitong, Tang, Zecong, et al. · arXiv (Cornell University) · 2
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VidUEU-Agent: A Data-Curation Agent for Multimodal Understanding, Editing, and Unified Tasks
2026 · Ru, Tengju, Lian, Weitong, et al. · arXiv (Cornell University)
HiSTEVE 1.0: Harnessing Human-Interface VLA Agents for Open-World Games
2026 · Tang, Zecong, Guan, Zian, et al. · arXiv (Cornell University)
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What Generation Knows: Unlocking Fine-Grained Understanding in Unified Multimodal Models
2026 · Ru, Tengju, Lian, Weitong, et al. · arXiv (Cornell University)
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Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design
2026 · Zong, Qing, Liu, Jiayu, et al. · arXiv (Cornell University)
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IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation
2026 · Meng, Lingyi, Tang, Zecong, et al. · arXiv (Cornell University)
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Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action
2026 · Zhang, Yi, Chen, Yinda, et al. · arXiv (Cornell University)
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Prediction of River Cross Section Morphology Below Water Surface Based on Deep Learning
2026 · Tang Zecong, Ma Yicheng, et al. · IAHR Asia-Pacific Division Congress (IAHR-APD)
Prediction of River Cross Section Morphology Below Water Surface Based on Deep Learning
2026 · Tang Zecong, Ma Yicheng, et al. · IAHR Asia-Pacific Division Congress (IAHR-APD)
RIVS-MORPHO Example Dataset
2026 · Tang, Zecong, Li, Haoran, et al. · Zenodo (CERN European Organization for Nuclear Research)
Imagine a City: CityGenAgent for Procedural 3D City Generation
2026 · Liu, Zishan, Tang, Zecong, et al. · arXiv (Cornell University)
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Drive-P2D: A Progressive Perception-to-Decision Benchmark for VLMs in Autonomous Driving
2026 · Tang, Zecong, Wang, Zixu, et al. · arXiv (Cornell University)
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PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments
2026 · Yuhao Zhan, Bingxiang He, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)
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Underwater River Cross Section Morphology Re-Construction: Training Strategies for Enhancing Domain Generalization in Deep Learning
2025 · Haoran Li, Rong Li, et al. · Proceedings of the IAHR World Congress
Works count: 14
Citation count: 2
H-index: 1
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