collaborators

5 papers

cs.CL2026

XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration

Nuo Chen, Andre Lin HuiKai, Jiaying Wu +5

Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality scientific writing. Most existing s…

cs.CR2026

ProtegoFed: Backdoor-Free Federated Instruction Tuning with Interspersed Poisoned Data

Haodong Zhao, Jinming Hu, Zhaomin Wu +7

Federated Instruction Tuning (FIT) enables collaborative instruction tuning of large language models across multiple organizations (clients) in a cross-silo setting without requiri…

cs.LG2026

Model-based Large Language Model Customization as Service

Zhaomin Wu, Jizhou Guo, Junyi Hou +3

Prominent Large Language Model (LLM) services from providers like OpenAI and Google excel at general tasks but often underperform on domain-specific applications. Current customiza…

cs.AI2026

PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing

Junyi Hou, Andre Lin Huikai, Nuo Chen +2

Large language models are increasingly embedded into academic writing workflows, yet existing assistants remain external to the editor, preventing deep interaction with document st…

cs.LG2025

Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly

Zhaomin Wu, Zhen Qin, Junyi Hou +4

Vertical Federated Learning (VFL) is a privacy-preserving collaborative learning paradigm that enables multiple parties with distinct feature sets to jointly train machine learning…