Papers by Allen Wu

2 papers
Visualizing Trends of Key Roles in News Articles (D19-3)

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Challenge: a demonstration system visualizes news trend of key roles based on natural language processing techniques . semantic role labelling and word embeddings can help users understand news topics .
Approach: They propose a system that visualizes the news trend of key roles based on natural language processing techniques.
Outcome: The proposed system analyzes the news trend of key roles using semantic role labelling . it also analyzes how similarities between key roles and news topics change over time .
GASim: A Graph-Accelerated Hybrid Framework for Social Simulation (2026.acl-long)

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Challenge: Large-scale social simulators require high latency due to expensive memory retrieval and sequential ABM execution.
Approach: They propose a graph-accelerated hybrid multi-agent framework for large-scale social simulations that uses large language models and numerical agent-based models to scale up simulations.
Outcome: The proposed framework delivers 9.94 speedup over the traditional framework and consumes less than 20% of tokens.

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