10 papers
Optimal-Agent-Selection: State-Aware Routing Framework for Efficient Multi-Agent Collaboration
Jingbo Wang, Sendong Zhao, Haochun Wang +2
The emergence of multi-agent systems powered by large language models (LLMs) has unlocked new frontiers in complex task-solving, enabling diverse agents to integrate unique experti…
Contractual Skills: A GovernSpec Design Framework for Enterprise AI Agents
Ting Liu
Skills have become a practical packaging mechanism for agent instructions, workflows, scripts, and reference materials. In enterprise settings, however, a skill often needs to expr…
Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection
Haochun Wang, Chaofen Yang, Jiatong Liu +5
In-context learning (ICL) is highly sensitive to which demonstrations appear in the prompt, but selecting them is expensive because the space of possible demonstration contexts and…
Orchestrating Intelligence: Confidence-Aware Routing for Efficient Multi-Agent Collaboration across Multi-Scale Models
Jingbo Wang, Sendong Zhao, Jiatong Liu +4
While multi-agent systems (MAS) have demonstrated superior performance over single-agent approaches in complex reasoning tasks, they often suffer from significant computational ine…
Uncovering the Role of Initial Saliency in U-Shaped Attention Bias: Scaling Initial Token Weight for Enhanced Long-Text Processing
Zewen Qiang, Sendong Zhao, Haochun Wang +2
Large language models (LLMs) have demonstrated strong performance on a variety of natural language processing (NLP) tasks. However, they often struggle with long-text sequences due…
MoGU V2: Toward a Higher Pareto Frontier Between Model Usability and Security
Yanrui Du, Fenglei Fan, Sendong Zhao +3
As Large Language Models (LLMs) increasingly permeate human life, their security has emerged as a critical concern, particularly their ability to maintain harmless responses to mal…