4 papers
Flexible Concept Bottleneck Model
Xingbo Du, Qiantong Dou, Lei Fan +1
Concept bottleneck models (CBMs) improve neural network interpretability by introducing an intermediate layer that maps human-understandable concepts to predictions. Recent work ha…
NPHardEval4V: Dynamic Evaluation of Large Vision-Language Models with Effects of Vision
Xiang Li, Wenyue Hua, Kaijie Zhu +8
Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in multimodal understanding, yet their reasoning abilities remain underexplored. Existing benchmarks…
SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence
Zhitao Zeng, Zhu Zhuo, Xiaojun Jia +12
Foundation models have achieved transformative success across biomedical domains by enabling holistic understanding of multimodal data. However, their application in surgery remain…
Large-scale artificial intelligence with 41 million nanophotonic neurons on a metasurface
Mingcheng Luo, Meirui Jiang, Bhavin J. Shastri +8
Conventional integrated circuits (ICs) struggle to meet the escalating demands of artificial intelligence (AI). This has sparked a renewed interest in an unconventional computing p…