122 citations · 244 across the 32 of their papers we have counts for
7 papers · 1 filter
Retrieval Meets Reasoning: Even High-school Textbook Knowledge Benefits Multimodal Reasoning
Cheng Tan, Jingxuan Wei, Linzhuang Sun +5
Large language models equipped with retrieval-augmented generation (RAG) represent a burgeoning field aimed at enhancing answering capabilities by leveraging external knowledge bas…
MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning
Zhe Li, Laurence T. Yang, Bocheng Ren +4
The scarcity of annotated data has sparked significant interest in unsupervised pre-training methods that leverage medical reports as auxiliary signals for medical visual represent…
Mitigating Prior Shape Bias in Point Clouds via Differentiable Center Learning
Zhe Li, Xiying Wang, Jinglin Zhao +3
Masked autoencoding and generative pretraining have achieved remarkable success in computer vision and natural language processing, and more recently, they have been extended to th…
Segment Anything in Defect Detection
Bozhen Hu, Bin Gao, Cheng Tan +2
Defect detection plays a crucial role in infrared non-destructive testing systems, offering non-contact, safe, and efficient inspection capabilities. However, challenges such as lo…
USTEP: Spatio-Temporal Predictive Learning under A Unified View
Cheng Tan, Jue Wang, Zhangyang Gao +2
Spatio-temporal predictive learning plays a crucial role in self-supervised learning, with wide-ranging applications across a diverse range of fields. Previous approaches for tempo…
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
Cheng Tan, Siyuan Li, Zhangyang Gao +5
Spatio-temporal predictive learning is a learning paradigm that enables models to learn spatial and temporal patterns by predicting future frames from given past frames in an unsup…