AgentPLM Enhances Protein Language Models
Topics
Developing
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Sources · 7 independent
“Differentiable Particle-Mesh Ewald with Cartesian Tensor Message Passing for Learning Long-Range Electrostatics and Dipole Response. Authors: Zhiyue Guo, Junjie Wang, Haoting Zhang, Zhixin Liang, Ziyang Yang, Yujian Pan, Jian Sun Abstract: Machine learning interatomic potentials (MLIPs) can approach quantum accuracy for short-rang...”
“Policy and World Modeling Co-Training for Language Agents. Authors: Ning Lu, Baijiong Lin, Shengcai Liu, Jiahao Wu, Haoze Lv, Yanbin Wei, Lingting Zhu, Shengju Qian, Xin Wang, Ying-Cong Chen and 2 others Abstract: Reinforcement learning (RL) improves large l...”
“AgentPLM: Agentic Protein Language Models with Reasoning-Augmented Decoding for Protein Sequence Design. Authors: Sahil Rahman, Maxx Richard Rahman Abstract: Protein language models (PLMs) are passive oracles: they generate sequences in a single forward pass with no mechanism to consult external biophys...”
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