expert selection

Coverage-Constrained Human-AI Cooperation with Multiple Experts AAAI 2026 Mixture-of-Trees: Learning to Select and Weigh Reasoning Paths for Efficient LLM Inference AAAI 2026 Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models AAAI 2026 Teacher-Guided Routing for Sparse Vision Mixture-of-Experts CVPR 2026 Discarding the Crutches: Adaptive Parameter-Efficient Expert Meta-Learning for Continual Semantic Parsing COLING 2025 Maximum Score Routing For Mixture-of-Experts ACL 2025 MultiPL-MoE: Multi-Programming-Lingual Extension of Large Language Models through Hybrid Mixture-of-Experts EMNLP 2025 Routing Experts: Learning to Route Dynamic Experts in Existing Multi-modal Large Language Models ICLR 2025 Divide and not forget: Ensemble of selectively trained experts in Continual Learning ICLR 2024 Harder Task Needs More Experts: Dynamic Routing in MoE Models ACL 2024 TensorOpera Router: A Multi-Model Router for Efficient LLM Inference EMNLP 2024 XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection ACL 2024 Learning When to Trust Which Teacher for Weakly Supervised ASR Interspeech 2023 Towards A Unified View of Sparse Feed-Forward Network in Pretraining Large Language Model EMNLP 2023 DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning NeurIPS 2021 Learning piecewise Lipschitz functions in changing environments AISTATS 2020 Distributed Non-Stochastic Experts NeurIPS 2012