10 citations · 21 across the 6 of their papers we have counts for
6 papers
S3C-LLM: Skill-Code Guided Agentic Language Models for Spectrum-to-Structure Elucidation
Xuanle Zhao, Xinyuan Cai, Xiang Cheng +1
Spectroscopic structure elucidation is central to molecular analysis, but recent Large Language Model (LLM)-based methods mostly formulate it as direct spectrum-to-SMILES generatio…
TinyChemVL: Advancing Chemical Vision-Language Models via Efficient Visual Token Reduction and Complex Reaction Tasks
Xuanle Zhao, Shuxin Zeng, Xinyuan Cai +4
While Vision Language Models (VLMs) have demonstrated remarkable capabilities in general visual understanding, their application in the chemical domain has been limited, with previ…
Neuromorphic Incremental on-chip Learning with Hebbian Weight Consolidation
Zifan Ning, Chaojin Chen, Xiang Cheng +3
As next-generation implantable brain-machine interfaces become pervasive on edge device, incrementally learning new tasks in bio-plasticity ways is urgently demanded for Neuromorph…
Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
With the Deep Neural Networks (DNNs) as a powerful function approximator, Deep Reinforcement Learning (DRL) has been excellently demonstrated on robotic control tasks. Compared to…
Finite Meta-Dynamic Neurons in Spiking Neural Networks for Spatio-temporal Learning
Xiang Cheng, Tielin Zhang, Shuncheng Jia +1
Spiking Neural Networks (SNNs) have incorporated more biologically-plausible structures and learning principles, hence are playing critical roles in bridging the gap between artifi…
Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagation
Tielin Zhang, Shuncheng Jia, Xiang Cheng +1
Spiking Neural Networks (SNNs) contain more biologically realistic structures and biologically-inspired learning principles than those in standard Artificial Neural Networks (ANNs)…