2 citations · 5 across the 9 of their papers we have counts for
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cs.LG2026★ 2 cited
Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis
Hao Li, He Cao, Shenyao Peng +7
Language models are revolutionizing the biochemistry domain, assisting scientists in drug design and chemical synthesis with high efficiency. Yet current approaches struggle betwee…
cs.LG2024
SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning
Jiying Zhang, Zijing Liu, Yu Wang +1
Molecular representation learning has shown great success in advancing AI-based drug discovery. The core of many recent works is based on the fact that the 3D geometric structure o…
cs.LG2023★ 2 cited
SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM
Jiayi Pan, Chengcan Wang, Kaifu Zheng +3
Large language models (LLMs) have shown remarkable capabilities in various tasks. However their huge model size and the consequent demand for computational and memory resources als…