5 accepted papers
Recent developments in brain recording are driving a demand for machine learning tools capable of decoding the latent structure of large populations of neurons. In this paper, we provide a comprehensive survey that outlines the trajectory of Latent Variable Models (LVMs) from early state-space model
``Read the room,'' or the ability to infer others' mental states from subtle social cues, is a hallmark of human social intelligence but remains a major challenge for current AI systems. Existing social reasoning datasets are limited in complexity, scale, and coverage of mental states, falling short…
Understanding the core dimensions of conceptual semantics is fundamental to uncovering how meaning is organized in language and the brain. Existing approaches often rely on predefined semantic dimensions that offer only broad representations, overlooking finer conceptual distinctions. This paper pro
We present a novel pipeline, ReflectEvo, to demonstrate that small language models (SLMs) can enhance meta introspection through reflection learning. This process iteratively generates self-reflection for self-training, fostering a continuous and self-evolving process. Leveraging this pipeline, we c…
Fabricated cellular micro-scaffold that recapitulates natural extracellular matrix (ECM) has shown huge potential in the study of cell behaviors. However, the reproducing of the physiological morphology with high efficiency and accuracy in the micro-scaffold still remains as a major challenge. Here,