This work proposes a multiagent belief state computation method termed mutual awareness belief (MAB), which extends belief modeling to decentralized partially observable settings by incorporating agents' behavioral intentions and collaborative relationships and proves effective in the nonmonotonic Pursuit environment.
Si-Han Zhou, Tian-Tian He, Yi-Nan Guo et al.· IEEE Transactions on Neural...· 0 citations
Modular Symbolic Regression with Physics Priors (MSR-PP), a knowledge-guided framework that conceptualizes one-dimensional PDEs as structured compositions of semantic modules (e.g., convection, diffusion) rather than random symbol sequences, is proposed.
Jinyang Du, Chunguo Wu, Xiao-Hu Shi et al.· Proceedings of the 32nd ACM...· 0 citations
Discovering governing Partial Differential Equations (PDEs) from observational data is a fundamental challenge in AI for Science. While Symbolic Regression (SR) dominates this task, existing token-level methods trigger a combinatorial explosion of search spaces, frequently yielding mathematically valid yet physically i...
Jinyang Du, Chunguo Wu, Xiaohu Shi et al.· Proceedings of the 32nd ACM...· 0 citations
The proposed ReliableRAG is the first reliability-driven framework that mitigates deceptive misinformation in multi-hop QA through fine-grained evaluation of individual triples, and quantifies triple reliability by combining query-triple semantic relevance with triple credibility.
Jingjing Jiang, Xuan Wu, Wen-Hao Song et al.· 0 citations
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