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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…
Synthetic Data Alone is Enough? Rethinking Data Scarcity in Pediatric Rare Disease Recognition
Ganlin Feng, Yuxi Long, Erin Lou +4
Children with rare genetic diseases often exhibit distinctive facial phenotypes, yet developing computer vision systems for early diagnosis remains challenging due to extreme data…
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…
Scaling-Aware Adapter for Structure-Grounded LLM Reasoning
Zihao Jing, Qiuhao Zeng, Ruiyi Fang +4
Large language models (LLMs) are enabling reasoning over 2D and 3D structures, yet existing methods remain modality-specific and typically compress structural inputs through sequen…