4 papers
GeoTLM: Geometry-aware Tactile-Language Models for Contact Motion Orientation Reasoning of Dynamic Objects
Qiutian Li, Zinan Liu, Lin Wang
Modern tactile-language models (TLMs) have shown potential for robot learning tasks, such as material and texture recognition. However, for contact-rich scenarios, these TLMs strug…
VL2Spike: Spike-driven Distillation from VLMs for Low-Power Visual Perception in Embodied AI
Zinan Liu, Eric Zheng, Soumyaratna Debnath +3
Spiking neural networks (SNNs) are brain-inspired, event-driven models that compute with sparse spikes, which enables highly efficient visual perception in resource-constrained emb…
LLMind: Bio-inspired Training-free Adaptive Visual Representations for Vision-Language Models
Soumyaratna Debnath, Bui Duc Manh, Zinan Liu +1
Vision-Language Models (VLMs) typically assume a uniform spatial fidelity across the entire field of view of visual inputs, dedicating equal precision to even the uninformative reg…
Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience
Zinan Liu, Haoran Li, Jingyi Lu +6
Autonomous AI is no longer a hard-to-reach concept, it enables the agents to move beyond executing tasks to independently addressing complex problems, adapting to change while hand…