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ARM: Attention with Routed-Memory for Learnable Sparse Control
Qiuhao Zeng, Jerry Huang, Peng Lu +7
Despite advances in long-context inference, large language models (LLMs) remain fundamentally limited by the key-value (KV) caching mechanisms that are necessary for stable computa…
Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding
Zihao Jing, Qiuhao Zeng, Ruiyi Fang +3
Molecular understanding is central to advancing areas such as scientific discovery, yet Large Language Models (LLMs) struggle to understand molecular graphs effectively. Existing g…
Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
Alana Deng, Sugitha Janarthanan, Yan Sun +2
Multiplex Biological Networks (MBNs), which represent multiple interaction types between entities, are crucial for understanding complex biological systems. Yet, existing methods o…
Pruning for Generalization: A Transfer-Oriented Spatiotemporal Graph Framework
Zihao Jing, Yuxi Long, Ganlin Feng
Multivariate time series forecasting in graph-structured domains is critical for real-world applications, yet existing spatiotemporal models often suffer from performance degradati…
Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning
Zihao Jing, Yan Sun, Yan Yi Li +3
Multimodal molecular models often suffer from 3D conformer unreliability and modality collapse, limiting their robustness and generalization. We propose MuMo, a structured multimod…
MolGraph-xLSTM: A graph-based dual-level xLSTM framework with multi-head mixture-of-experts for enhanced molecular representation and interpretability
Yan Sun, Yutong Lu, Yan Yi Li +3
Predicting molecular properties is essential for drug discovery, and computational methods can greatly enhance this process. Molecular graphs have become a focus for representation…