Minh Hoang Nguyen — accepted AI-conference papers

2026

Expert Merging in Sparse Mixture of Experts with Nash Bargaining

Dung Viet Nguyen, Anh Nguyen Thi, Minh Hoang Nguyen, Luc Nguyen, Shiqi Jiang, Ethan Fetaya +3

ICLR 2026poster

Existing expert merging strategies for Sparse Mixture of Experts (SMoE) typically rely on input-dependent or input-independent averaging of expert parameters, but often lack a principled weighting mechanism. In this work, we reinterpret expert merging through the lens of game theory, revealing coope…

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2025

Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer

Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal, Sunil Gupta, Hung Le

IJCAI 2025

Decision Transformers (DT) play a crucial role in modern reinforcement learning, leveraging offline datasets to achieve impressive results across various domains. However, DT requires high-quality, comprehensive data to perform optimally. In real-world applications, the lack of training data and the

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