5 papers
GenericAgent: A Token-Efficient Self-Evolving LLM Agent via Contextual Information Density Maximization (V1.0)
Jiaqing Liang, Jinyi Han, Weijia Li +15
Long-horizon large language model (LLM) agents are fundamentally limited by context. As interactions become longer, tool descriptions, retrieved memories, and raw environmental fee…
RiboSphere: Learning Unified and Efficient Representations of RNA Structures
Zhou Zhang, Hanqun Cao, Cheng Tan +3
Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimentally determined 3D structures a…
DERM-3R: A Resource-Efficient Multimodal Agents Framework for Dermatologic Diagnosis and Treatment in Real-World Clinical Settings
Ziwen Chen, Zhendong Wang, Chongjing Wang +12
Dermatologic diseases impose a large and growing global burden, affecting billions and substantially reducing quality of life. While modern therapies can rapidly control acute symp…
RiboPO: Preference Optimization for Structure- and Stability-Aware RNA Design
Minghao Sun, Hanqun Cao, Zhou Zhang +10
Designing RNA sequences that reliably adopt specified three-dimensional structures while maintaining thermodynamic stability remains challenging for synthetic biology and therapeut…
From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning?
Hanqun Cao, Hongrui Zhang, Junde Xu +12
Protein language models (PLMs) have advanced computational protein science through large-scale pretraining and scalable architectures. In parallel, reinforcement learning (RL) has…