activity
20232026
most citedChannel-Wise Mixed-Precision Quantization for Large Language Models

2 citations · 3 across the 20 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.CV2026

UniMod: Enhancing Multi-Modal Medical Diagnosis through Cross-Modality and Within-Modality Alignment

Zijian Gu, Weikai Lin, Shuang Zhou +2

Multi-modal learning combining medical images and clinical text is promising for disease diagnosis. However, standard multi-modal training leads to shortcut learning: models exploi…

cs.AI2026

The Past Is Prologue: A Plug-in Controller for Selective Updates in Sequentially Evolving LLM Memory

Zihan Chen, Songwei Dong, Chengshuai Shi +4

Sequentially evolving LLM memory enables agents to reuse past experience, but existing systems usually deploy each locally generated memory update without checking whether it impro…

cs.LG2026

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory

Songwei Dong, Zihan Chen, Chengshuai Shi +3

Memory plays a central role in enabling large language models (LLMs) to operate over sequential tasks by accumulating and reusing experience over time. However, existing evaluation…

cs.LG2026

Generalist Graph Anomaly Detection via Prototype-Based Distillation

Yiming Xu, Zihan Chen, Zhen Peng +4

Driven by the pressing demand for graph anomaly detection (GAD) in high-stakes domains, the generalist GAD paradigm, which trains a single detector transferable across new graphs,…

cs.LG2026

Lean Clients, Full Accuracy: Hybrid Zeroth- and First-Order Split Federated Learning

Zhoubin Kou, Zihan Chen, Jing Yang +1

Split Federated Learning (SFL) enables collaborative training between resource-constrained edge devices and a compute-rich server. Communication overhead is a central issue in SFL…