10 papers
A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks
Silin Chen, Yuzhong Chen, Caiwei Wang +9
Whether artificial neural networks organize information comparably to the human brain remains unclear. Prior brain--AI alignment studies are constrained by specific inputs and task…
iGSP:Implicit Gradient Subspace Projection for Efficient Continual Learning of Vision-Language Models
Xuezhi Cui, Dongbo Zhou, Wang Guo +8
Vision-Language Models require efficient adaptation to continually emerging downstream tasks. While Parameter-Efficient Fine-Tuning mitigates catastrophic forgetting, assigning iso…
A World Model of Radiologist Reading for Medical Image Representation Learning
Yiwei Li, Zihao Wu, Huaqin Zhao +5
Radiologist eye-tracking data provide a rich record of how experts search, compare, and accumulate evidence during image reading; yet, existing methods exploit this signal only par…
Drift Flow Matching
Chenrui Ma, Xi Xiao, Lin Zhao +3
Iterative generative models such as Flow Matching and Diffusion models have demonstrated strong test-time scaling behavior, where additional inference computation can improve gener…
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Juyi Lin, Arash Akbari, Yumei He +13
Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…
Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems
Sohan Shankar, Yi Pan, Hanqi Jiang +43
This position and survey paper identifies the emerging convergence of neuroscience, artificial general intelligence (AGI), and neuromorphic computing toward a unified research para…