1 citations · 1 across the 12 of their papers we have counts for
12 papers
Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning
Shanyong Wang, Shuhang Lin, Yining Zhao +2
Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major challenge remains in adapting L…
RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routing
Ziqi Wang, Xi Zhu, Shuhang Lin +3
Retrieval-augmented generation (RAG) has evolved into a family of paradigms with distinct performance profiles and resource demands, turning paradigm selection into a multi-criteri…
CTkvr: KV Cache Retrieval for Long-Context LLMs via Centroid then Token Indexing
Kuan Lu, Shuhang Lin, Sai Wu +7
Large language models (LLMs) are increasingly applied in long-context scenarios such as multi-turn conversations. However, long contexts pose significant challenges for inference e…
Cache Mechanism for Agent RAG Systems
Shuhang Lin, Zhencan Peng, Lingyao Li +3
Recent advances in Large Language Model (LLM)-based agents have been propelled by Retrieval-Augmented Generation (RAG), which grants the models access to vast external knowledge ba…
Node-as-Agent: Graph Agentic Network
Minghao Guo, Xi Zhu, Qingyue Jiao +7
Graph Neural Networks (GNNs) have achieved remarkable success in graph-based learning by propagating information among neighbor nodes via predefined aggregation mechanisms. However…
Know the Ropes: A Heuristic Strategy for LLM-based Multi-Agent System Design
Zhenkun Li, Lingyao Li, Shuhang Lin +1
Single-agent LLMs hit hard limits--finite context, role overload, and brittle domain transfer. Conventional multi-agent fixes soften those edges yet expose fresh pains: ill-posed d…
Invisible Prompts, Visible Threats: Malicious Font Injection in External Resources for Large Language Models
Junjie Xiong, Changjia Zhu, Shuhang Lin +4
Large Language Models (LLMs) are increasingly equipped with capabilities of real-time web search and integrated with protocols like Model Context Protocol (MCP). This extension cou…
LiteCUA: Computer as MCP Server for Computer-Use Agent on AIOS
Kai Mei, Xi Zhu, Hang Gao +2
We present AIOS 1.0, a novel platform designed to advance computer-use agent (CUA) capabilities through environmental contextualization. While existing approaches primarily focus o…
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense
Yang Ouyang, Hengrui Gu, Shuhang Lin +6
As large language models (LLMs) are increasingly deployed in diverse applications, including chatbot assistants and code generation, aligning their behavior with safety and ethical…
OmniRouter: Budget and Performance Controllable Multi-LLM Routing
Kai Mei, Wujiang Xu, Minghao Guo +2
Large language models (LLMs) deliver superior performance but require substantial computational resources and operate with relatively low efficiency, while smaller models can effic…
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilities
Wenyue Hua, Kaijie Zhu, Lingyao Li +7
This study intends to systematically disentangle pure logic reasoning and text understanding by investigating the contrast across abstract and contextualized logical problems from…
BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis
Shuhang Lin, Wenyue Hua, Lingyao Li +7
This paper presents BattleAgent, an emulation system that combines the Large Vision-Language Model and Multi-agent System. This novel system aims to simulate complex dynamic intera…