265 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shanghai Jiao Tong UniversityCN12 papers
- Fudan UniversityCN8 papers
- University of Science and Technology of ChinaCN5 papers
- CAS Key Laboratory of Urban Pollutant ConversionCN3 papers
- Shanghai Artificial Intelligence LaboratoryCN3 papers
- Shanghai Fudan Microelectronics (China)CN3 papers
- Beijing Academy of Artificial IntelligenceCN2 papers
- Chinese Academy of SciencesCN2 papers
- Institute of Computing TechnologyCN2 papers
- Nanjing UniversityCN2 papers
- Shanghai UniversityCN2 papers
- Southern University of Science and TechnologyCN2 papers
6 papers · 1 filter
A General-Purpose Framework for Chemical Reaction Representation with Atomic Correspondence and Flexible Condition Adaptation
Kaipeng Zeng, Xianbin Liu, Yu Zhang +3
Motivation: Organic synthesis is fundamental to the chemical industry, particularly in domains such as pharmaceutical development. While artificial intelligence offers powerful too…
TensorTEE: Unifying Heterogeneous TEE Granularity for Efficient Secure Collaborative Tensor Computing
Husheng Han, Xinyao Zheng, Yuanbo Wen +11
Heterogeneous collaborative computing with NPU and CPU has received widespread attention due to its substantial performance benefits. To ensure data confidentiality and integrity d…
Vehicles Swarm Intelligence: Cooperation in both Longitudinal and Lateral Dimensions
Jia Hu, Nuoheng Zhang, Haoran Wang +3
Longitudinal-only platooning methods are facing great challenges on running mobility, since they may be impeded by slow-moving vehicles from time to time. To address this issue, th…
Towards free-response paradigm: a theory on decision-making in spiking neural networks
Zhichao Zhu, Yang Qi, Wenlian Lu +3
The energy-efficient and brain-like information processing abilities of Spiking Neural Networks (SNNs) have attracted considerable attention, establishing them as a crucial element…
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework
Kaiyan Chang, Kun Wang, Nan Yang +16
Recent advances in large language models have demonstrated their potential for automated generation of hardware description language (HDL) code from high-level prompts. Researchers…
MULTI: Multimodal Understanding Leaderboard with Text and Images
Zichen Zhu, Yang Xu, Lu Chen +11
The rapid development of multimodal large language models (MLLMs) raises the question of how they compare to human performance. While existing datasets often feature synthetic or o…