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VCLMU: Mechanism-Centric Virtual Cell World Modeling for Perturbation Response
Yuwei Miao, Azim Dehghani Amirabad, Scott Oloff +3
Predicting cellular responses to genetic perturbations is a central capability for virtual cells and a key step toward computational modeling of biological interventions. Most exis…
EGSD: Event-Grounded Self-Distillation for Streaming Video Understanding
Yuwei Miao, Xuesheng Zhang, Wenhao Zou +5
Real-time video understanding requires incrementally maintaining a memory of streaming content, and optimizing this requires dense process signals. On-Policy Self-Distillation (OPS…
EAPO: Entropy-Driven Adaptive Positive-Negative Sample Weighting for Policy Optimization in Open-Ended QA
Yunsheng Zeng, Gen Li, Yuwei Miao +8
Large Reasoning Models are typically trained via reinforcement learning from verifiable rewards (RLVR). However, existing approaches adopt fixed weights for positive and negative s…
C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning
Yuwei Miao, Gen Li, Yunsheng Zeng +8
Retrieval-augmented generation (RAG) trained with reinforcement learning (RL) is a promising way to ground large language models in medical evidence for clinical diagnosis. However…
scpFormer: A Foundation Model for Unified Representation and Integration of the Single-Cell Proteomics
Qifeng Zhou, Lei Yu, Yuzhi Guo +5
The integration of single-cell proteomic data is often hindered by the fragmented nature of targeted antibody panels. To address this limitation, we introduce scpFormer, a transfor…