1 citations · 1 across the 11 of their papers we have counts for
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An Infectious Disease Spread Simulation Based on Large Language Model Decision Making
Yonchanok Khaokaew, Ruochen Kong, Andreas Zufle +6
Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective public health interventions. Prio…
MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs
Ruiyi Yang, Zechen Li, Hao Xue +2
Self-evolving language-model agents must decide what to learn next and how to preserve what they have learned across iterations. Existing systems typically carry this cross-iterati…
SOCIA-: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation
Yuncheng Hua, Sion Weatherhead, Mehdi Jafari +2
In this paper, we present SOCIA-, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph.…
SOCIA-Nabla: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation
Yuncheng Hua, Sion Weatherhead, Mehdi Jafari +2
In this paper, we present SOCIA-Nabla, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph. Spe…
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
Ruiyi Yang, Hao Xue, Imran Razzak +3
Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy trade-offs when scaling to large kn…
Beyond Single Pass, Looping Through Time: KG-IRAG with Iterative Knowledge Retrieval
Ruiyi Yang, Hao Xue, Imran Razzak +2
Graph Retrieval-Augmented Generation (GraphRAG) has proven highly effective in enhancing the performance of Large Language Models (LLMs) on tasks that require external knowledge. B…