TY - GEN
T1 - Schema-Guided Culture-Aware Complex Event Simulation with Multi-Agent Role-Play
AU - Li, Sha
AU - Reddy, Revanth Gangi
AU - Nguyen, Khanh Duy
AU - Wang, Qingyun
AU - Fung, May
AU - Han, Chi
AU - Han, Jiawei
AU - Natarajan, Kartik
AU - Voss, Clare R.
AU - Ji, Heng
N1 - This research is based upon work supported by DARPA KAIROS Program No. 18 FA8750-19-2-1004, DARPA SemaFor Program No. HR001120C0123, DARPA CCU Program No. HR001122C0034, DARPA ITM Program No. FA8650-23-C-7316 and DARPA INCAS Program No. HR001121C0165. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of DARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein.
PY - 2024
Y1 - 2024
N2 - Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society. Relying on historical events to project the future is insufficient as such events are sparse and do not cover all possible conditions and nuanced situations. Simulation of these complex events can help better prepare and reduce the negative impact. We develop a controllable complex news event simulator guided by both the event schema representing domain knowledge about the scenario and user-provided assumptions representing case-specific conditions. As event dynamics depend on the fine-grained social and cultural context, we further introduce a geo-diverse commonsense and cultural norm-aware knowledge enhancement component. To enhance the coherence of the simulation, apart from the global timeline of events, we take an agent-based approach to simulate the individual character states, plans, and actions. By incorporating the schema and cultural norms, our generated simulations achieve much higher coherence and appropriateness and are received favorably by participants from a humanitarian assistance organization.
AB - Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society. Relying on historical events to project the future is insufficient as such events are sparse and do not cover all possible conditions and nuanced situations. Simulation of these complex events can help better prepare and reduce the negative impact. We develop a controllable complex news event simulator guided by both the event schema representing domain knowledge about the scenario and user-provided assumptions representing case-specific conditions. As event dynamics depend on the fine-grained social and cultural context, we further introduce a geo-diverse commonsense and cultural norm-aware knowledge enhancement component. To enhance the coherence of the simulation, apart from the global timeline of events, we take an agent-based approach to simulate the individual character states, plans, and actions. By incorporating the schema and cultural norms, our generated simulations achieve much higher coherence and appropriateness and are received favorably by participants from a humanitarian assistance organization.
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U2 - 10.18653/v1/2024.emnlp-demo.39
DO - 10.18653/v1/2024.emnlp-demo.39
M3 - Conference contribution
AN - SCOPUS:85216564350
T3 - EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of System Demonstrations
SP - 372
EP - 381
BT - EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of System Demonstrations
A2 - Farias, Delia Irazu Hernandez
A2 - Hope, Tom
A2 - Li, Manling
PB - Association for Computational Linguistics (ACL)
T2 - 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, EMNLP 2024
Y2 - 12 November 2024 through 16 November 2024
ER -