Chen, Guanzheng

Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Leng, S., Zhang, H., Chen, G., Li, X., Lu, S., Miao, C., & Bing, L. (2023) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 199

Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Leng, S., Zhang, H., Chen, G., Li, X., Lu, S., Miao, C., & Bing, L. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 199

Revisiting Parameter-Efficient Tuning: Are We Really There Yet?

Chen, G., Liu, F., Meng, Z., & Liang, S. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 60

VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Zhang, B., Li, K., Cheng, Z., Hu, Z., Yuan, Y., Chen, G., Leng, S., Jiang, Y., Zhang, H., Li, X., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 5

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

Meng, F., Du, L., Wu, Z., Chen, G., Liu, X., Liao, J., Jiang, C., Wan, Z., Gu, J., Zhou, P., et al. (2026) · arXiv

AI-based Problem Solving and PlanningSpeech and dialogue systems

Cited by 0