4 papers
Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation
Mingxuan Ouyang, Hao Lan, Wanyu Lin
Leveraging large language models (LLMs) for molecular generation has shown remarkable potential in chemical and drug design. Current methods primarily rely on supervised training o…
Accelerating AIGC Services with Latent Action Diffusion Scheduling in Edge Networks
Changfu Xu, Jianxiong Guo, Wanyu Lin +5
Artificial Intelligence Generated Content (AIGC) has gained significant popularity for creating diverse content. Current AIGC models primarily focus on content quality within a cen…
Exploiting Latent Linearity in LLMs Improves Explainable Molecular Representation Learning
Zhuoran Li, Xu Sun, Wanyu Lin +1
Large language models (LLMs) have demonstrated broad utility across molecular domains, spanning drug discovery and materials design. Analyzing LLMs' latent representations is cruci…
Debiasing Graph Representation Learning based on Information Bottleneck
Ziyi Zhang, Mingxuan Ouyang, Wanyu Lin +2
Graph representation learning has shown superior performance in numerous real-world applications, such as finance and social networks. Nevertheless, most existing works might make…