collaborators

8 papers

cs.CR2026

Agent-Assisted Side-Channel Attacks on Non-Prefix KV Cache in RAG

He Sun, Shinan Liu, Siyuan Ma +3

Modern Large Language Model (LLM) serving engines increasingly rely on Retrieval-Augmented Generation (RAG) and non-prefix Key-Value (KV) cache fusion to accelerate long-context, m…

cs.AI2026

MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing

Chuang Tang, Chenhao Lin, Yin Xu +5

Parsing chemical reaction diagrams from scientific literature is challenging due to heterogeneous layouts, intertwined visual elements, and the difficulty of integrating recognitio…

cs.AR2026

HillInfer: Efficient Long-Context LLM Inference on the Edge with Hierarchical KV Eviction using SmartSSD

He Sun, Shinan Liu, Li Li +1

Deploying Large Language Models (LLMs) on memory-constrained AI Personal Computers (AIPCs) enables low-latency, privacy-preserving inference, but long-context generation is fundame…

cs.LG2026

CooperLLM: Cloud-Edge-End Cooperative Federated Fine-tuning for LLMs via ZOO-based Gradient Correction

He Sun, Jinrui Zhou, Li Li +1

Large Language Models (LLMs) perform well on many NLP tasks, but fine-tuning them on resource-constrained mobile devices is challenging due to high memory and computation costs, de…

cs.AI2025

Enhancing Automated Paper Reproduction via Prompt-Free Collaborative Agents

Zijie Lin, Qilin Cai, Liang Shen +1

Automated paper reproduction has emerged as a promising approach to accelerate scientific research, employing multi-step workflow frameworks to systematically convert academic pape…

cs.LG2025

SFedKD: Sequential Federated Learning with Discrepancy-Aware Multi-Teacher Knowledge Distillation

Haotian Xu, Jinrui Zhou, Xichong Zhang +3

Federated Learning (FL) is a distributed machine learning paradigm which coordinates multiple clients to collaboratively train a global model via a central server. Sequential Feder…