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20242026
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cs.LG2025

Vulnerability-Aware Robust Multimodal Adversarial Training

Junrui Zhang, Xinyu Zhao, Jie Peng +3

Multimodal learning has shown significant superiority on various tasks by integrating multiple modalities. However, the interdependencies among modalities increase the susceptibili…

cs.LG2025

Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design

Mohan Zhang, Pingzhi Li, Jie Peng +2

Mixture-of-Experts (MoE) has successfully scaled up models while maintaining nearly constant computing costs. By employing a gating network to route input tokens, it selectively ac…

cs.LG2025

GRNFormer: A Biologically-Guided Framework for Integrating Gene Regulatory Networks into RNA Foundation Models

Mufan Qiu, Xinyu Hu, Fengwei Zhan +6

Foundation models for single-cell RNA sequencing (scRNA-seq) have shown promising capabilities in capturing gene expression patterns. However, current approaches face critical limi…

cs.LG2025

Continually Evolved Multimodal Foundation Models for Cancer Prognosis

Jie Peng, Shuang Zhou, Longwei Yang +7

Cancer prognosis is a critical task that involves predicting patient outcomes and survival rates. To enhance prediction accuracy, previous studies have integrated diverse data moda…

cs.LG2024

Harnessing Your DRAM and SSD for Sustainable and Accessible LLM Inference with Mixed-Precision and Multi-level Caching

Jie Peng, Zhang Cao, Huaizhi Qu +5

Although Large Language Models (LLMs) have demonstrated remarkable capabilities, their massive parameter counts and associated extensive computing make LLMs' deployment the main pa…